CodingMercor
Mercor’s Talent Success team is hiring! Our Talent Success team is responsible for ensuring everyone using our platform has a delightful experience end to end, from applying to job listings, taking our AI-led interviews, accepting offers on our platform, and getting paid for their hard work.
Note: This role is open only to candidates currently residing in Latin America. Applicants outside Latin America will not be considered.
About the Role
Mercor has thousands of users joining the platform each week to interview for different roles our clients have posted. When they run into issues or have questions and reach out for help, you will be responsible for giving them a speedy and delightful experience.
You will work directly with our engineering team, triaging and investigating bug reports so being super savvy with modern websites and issues SaaS-type applications run into will come in handy.
Since your conversations with the talent applying on our platform will often be the first interaction someone has with Mercor, maintaining an enthusiastic, upbeat tone while writing at native English level proficiency is important. We use a lighthearted and informal tone in our support communication while at the same time being very professional and precise in our replies.
Note: This is a remote, 6-day/week role requiring substantial overlap with Pacific Time (PT/PST) working hours.
Key Responsibilities
Investigate talent-reported issues end-to-end: reproduce bugs, identify root causes, and separate UX friction, model edge cases, and system defects.
Debug across our AI + SaaS stack using telemetry, logs, network inspection, and database queries to understand production behavior.
Triage with sound judgment — escalate true engineering issues and resolve others via configuration, prompt refinement, or clear user guidance.
Surface systemic patterns and product risks to engineering and product leadership.
Create clear documentation and runbooks to reduce repeat issues and improve resolution speed.
Communicate with precision, professionalism, and empathy.
Qualifications
Ability to debug web applications, likely coming from either a
Degree in Computer Science, Software Engineering, or a related technical field from a top-tier institution or prior experience at a high-growth technology startup.
Experience building modern web applications (React, Node, Flask, Next.js, etc.) OR
2-5 years of experience supporting customers on such web applications.
Comfortable with _AI systems_ — you’ve played with LLMs, agents, or generative models.
Experience exploring behavior of AI tools (fine-tuning, prompt chains, chain-of-thought debugging, or building agents).
Ability to understand model outputs, failure modes, hallucinations, and feedback loops.
Familiarity with how modern AI APIs work (OpenAI, Anthropic, etc.) or how agent frameworks (LangChain, AutoGPT, etc.) function is a plus.
About Mercor
Mercor is at the intersection of labor markets and AI research. We partner with leading AI labs and enterprises to provide the human intelligence essential to AI development.
Our vast talent network trains frontier AI models in the same way teachers teach students: by sharing knowledge, experience, and context that can't be captured in code alone. Today, more than 30,000 experts in our network collectively earn over $2 million a day.
Mercor is creating a new category of work where expertise powers AI advancement. Achieving this requires an ambitious, fast-paced and deeply committed team. You’ll work alongside researchers, operators, and AI companies at the forefront of shaping the systems that are redefining society.
Mercor is a profitable Series C company valued at $10 billion.
Full-time· Remote (Mexico, CRI, SLV, GTM, PAN, ARG, BOL, Brazil, CHL, COL, ECU, GUY, PRY, PER, and URY)
Status: Open
CodingMercor
Mercor’s Talent Success team is hiring! Our Talent Success team is responsible for ensuring everyone using our platform has a delightful experience end to end, from applying to job listings, taking our AI-led interviews, accepting offers on our platform, and getting paid for their hard work.
About the Role
Mercor has thousands of users joining the platform each week to interview for different roles our clients have posted. When they run into issues or have questions and reach out for help, you will be responsible for giving them a speedy and delightful experience.
You will work directly with our engineering team, triaging and investigating bug reports so being super savvy with modern websites and issues SaaS-type applications run into will come in handy.
Since your conversations with the talent applying on our platform will often be the first interaction someone has with Mercor, maintaining an enthusiastic, upbeat tone while writing at native English level proficiency is important. We use a lighthearted and informal tone in our support communication while at the same time being very professional and precise in our replies.
Note: This is a remote, 6-day/week role requiring substantial overlap with Pacific Time (PT/PST) working hours.
Key Responsibilities
Investigate talent-reported issues end-to-end: reproduce bugs, identify root causes, and separate UX friction, model edge cases, and system defects.
Debug across our AI + SaaS stack using telemetry, logs, network inspection, and database queries to understand production behavior.
Triage with sound judgment — escalate true engineering issues and resolve others via configuration, prompt refinement, or clear user guidance.
Surface systemic patterns and product risks to engineering and product leadership.
Create clear documentation and runbooks to reduce repeat issues and improve resolution speed.
Communicate with precision, professionalism, and empathy.
Qualifications
Ability to debug web applications, likely coming from either a
Degree in Computer Science, Software Engineering, or a related technical field from a top-tier institution or prior experience at a high-growth technology startup.
Experience building modern web applications (React, Node, Flask, Next.js, etc.) OR
2-5 years of experience supporting customers on such web applications.
Comfortable with _AI systems_ — you’ve played with LLMs, agents, or generative models.
Experience exploring behavior of AI tools (fine-tuning, prompt chains, chain-of-thought debugging, or building agents).
Ability to understand model outputs, failure modes, hallucinations, and feedback loops.
Familiarity with how modern AI APIs work (OpenAI, Anthropic, etc.) or how agent frameworks (LangChain, AutoGPT, etc.) function is a plus.
About Mercor
Mercor is at the intersection of labor markets and AI research. We partner with leading AI labs and enterprises to provide the human intelligence essential to AI development.
Our vast talent network trains frontier AI models in the same way teachers teach students: by sharing knowledge, experience, and context that can't be captured in code alone. Today, more than 30,000 experts in our network collectively earn over $2 million a day.
Mercor is creating a new category of work where expertise powers AI advancement. Achieving this requires an ambitious, fast-paced and deeply committed team. You’ll work alongside researchers, operators, and AI companies at the forefront of shaping the systems that are redefining society.
Mercor is a profitable Series C company valued at $10 billion.
Full-time· Remote
Status: Open
Expert WorkMercor
Mercor’s Talent Success team is hiring! Our Talent Success team is responsible for ensuring everyone using our platform is having a delightful experience end to end, from applying to job listings, taking our AI-led interviews, accepting offers on our platform, and getting paid for their hard work.
About the Role
Mercor has thousands of users joining the platform each week to interview for different roles our clients have posted. When they run into issues or have questions and reach out for help, you will be responsible for giving them a speedy and delightful experience.
You will work directly with our engineering team, triaging and investigating bug reports so being super savvy with modern websites and issues SaaS-type applications run into will come in handy.
Since your conversations with the talent applying on our platform will often be the first interaction someone has with Mercor, maintaining an enthusiastic, upbeat tone while writing at native English level proficiency is important. We use a lighthearted and informal tone in our support communication while at the same time being very professional and precise in our replies.
Note: This is a full time employment opportunity with Mercor India.
Key Responsibilities
Respond to support requests from Mercor’s talent pool who have a question or issue applying for roles on our platform
Triage and investigate talent-reported issues. Identify redundancies and plan-execute-monitor day to day talent success workflows for improving experience for our talent where it matters the most.
Proactively identify and document recurring user pain points/issues, sharing actionable insights with product and engineering teams to reduce support volume and improve self-serve experiences
Build talent-facing documentation to answer common questions we get in our support queue
Advocate for our users internally—help shape the product by championing their feedback and needs.
Maintain enthusiasm and positivity while writing replies in near-perfect English
Qualifications
1–3 years of experience in customer success, operations, or product support in a SaaS or marketplace environment
Strong communication and problem-solving skills, with a proven ability to de-escalate issues and keep users happy.
Experience using a support platform (like Zendesk, Intercom, Help Scout, Freshdesk, Crisp)
Natural product intuition—you notice friction points, think through solutions, and can articulate them clearly to non-support teams
Comfort working cross-functionally to drive resolutions through process or product improvements rather than manual fixes
At Mercor, we recognize that exceptional ability comes in all forms, a core philosophy on which we built our platform. Because of this, we welcome candidates from diverse backgrounds with unique experiences and transferable skill sets, even if they don't meet all the preferred qualifications listed above.
About Mercor
Founded in 2023, Mercor is advancing the frontier of AI with human intelligence. Millions of domain experts on the platform are paid over $4 million per day to train frontier AI models. Mercor's APEX benchmark family measures AI's real-world impact on professional work, and Mercor Enterprise brings the same expert network and evaluation infrastructure to Fortune 500 companies deploying AI in production.
We consider all qualified applicants without regard to legally protected characteristics and provide reasonable accommodations upon request.
Full-time· Remote
Status: Open
CodingMercor
Applications close Friday, October 16, 2026 at 12:00 p.m. Pacific. We are selecting the first three applicants who qualify for the initial pilot.
About the work
Build real-world tasks that test how well AI agents handle database engineering. Depending on your specialty, your task may cover database-engine implementation, production diagnosis, or application migration.
Each task should include a clear problem statement, a reproducible repository or environment, a working reference solution, tests, and grading criteria that distinguish a robust engineering solution from one that only appears correct.
What you'll do
Design one challenging, self-contained database engineering task.
Build checks for correctness, failure handling, concurrency, retries, and regressions where relevant.
Evaluate performance measures such as latency, throughput, and memory use.
Write clear grading criteria for engineering judgment.
Work with technical reviewers to refine and validate the task.
Who we're looking for
At least five years of hands-on database-engine internals experience, or a database-systems PhD.
Deep experience with storage engines, query execution, optimization, transactions, replication, or related low-latency systems.
Strong implementation skills and clear explanations of correctness and performance tradeoffs.
Experience with Go is preferred.
DBA, SQL analytics, ETL, or application-only database experience does not qualify on its own. You do not need to specialize in every task area.
Application process
Complete a self-paced technical assessment with written responses and a coding exercise. You control when to advance between sections. (~35 min)
Use a laptop or desktop with a camera, microphone, and entire-screen sharing. Have your own editor and terminal ready, along with Python 3.8+ and a compiler for C, C++, Rust, Go, or Java. The assessment includes a starter kit and public tests. Complete the assessment independently, without outside AI assistance.
Please apply as soon as possible. We will select the first three qualifying applicants. If the pilot fills, completed assessments may be considered for future work if the project expands.
Paid task after selection
Selected experts will complete one task, with approximately 25 hours of work, followed by technical review and feedback.
Task deadline: Friday, October 30, 2026.
Task-based· Remote
Status: Open
CodingMercor
We are looking for engineers who build and operate LLM agents in production, and who have real visibility into how agents are actually used inside a company.
You have probably:
Shipped an agent that real users depended on, and been on the hook when it broke.
Figured out how to tell whether an agent got better or worse after a change.
Run agents that outlive a single request: scheduled jobs, long-running work, cloud sandboxes.
Watched your org build an internal assistant, and seen who adopted it and who quietly did not.
We are especially interested in the layers most people do not talk about: internal monoagents wired into company data, shared company memory, reusable skills and playbooks, the tool and MCP surfaces agents call, and how anyone sees what agents did and what they cost.
Applying starts with a short conversational AI interview. No coding, no take-home. We want to hear how you actually think about agent reliability, evaluation, and adoption, and the tradeoffs you have made in real systems. Bring war stories. The messier and more specific, the better.
If that screen stands out, we will invite you to a live 30 minute conversation with our team. We pay $100 to $500 for that conversation, paid on completion of the call, with the amount depending on depth of experience.
If that sounds like you, apply and complete the screen. We review every submission.
Task-based· Remote
Status: Open
Expert WorkMercor
1\. Role Overview
Mercor is collaborating with a leading AI research lab on a project to advance frontier medical problem-solving in oncology. We are looking for oncologists based in the United States with hands-on clinical practice experience. The goal of this project is to identify gaps in AI model reasoning around real-world oncology cases, particularly in clinical trial design, patient eligibility, and treatment decision-making, and to support the training of cutting-edge AI models.
This is a short-term, high-impact, remote opportunity for oncologists excited about applying their clinical expertise to frontier AI research, with the possibility of extension based on performance.
2\. Key Responsibilities
Create realistic, nuanced oncology tasks and scenarios, particularly around clinical trials, that expose weaknesses in frontier AI model responses
Evaluate AI-generated clinical reasoning for accuracy, completeness, and alignment with current standard-of-care guidelines
Identify flawed logic, missed diagnoses, incomplete treatment rationale, or unsafe recommendations in model outputs
Provide clear, well-structured expert responses and chain-of-thought reasoning that reflect real clinical decision-making
3\. Qualifications
You are a strong fit for this project if you meet most or all of the following:
MD or DO who is currently pursuing or has completed a fellowship in medical oncology or hematology/oncology
Currently practicing in the United States and seeing oncology patients, or has done so within the past three years (3+ years of post-residency experience strongly preferred)
Ability to articulate clinical reasoning clearly and precisely in written form
Contractor· Remote (United States)
Status: Open
Expert WorkMercor
About the work
We are building expert-authored forecasting and research data used to evaluate and improve AI models on real macro analysis. Each task asks a practitioner to reason from a fixed evidence cutoff — no hindsight — and document the judgment a strong analyst would have made at that moment.
This role covers non-G7 central bank communication. We staff separately by country: a broad global-macro profile is not enough, and we are looking for depth on one specific central bank.
What you will do
Interpret statements, minutes, speeches and wording changes from a specific non-G7 central bank in their source language
Compare current language against prior guidance and prevailing market expectations
Assign a calibrated dovish-to-hawkish score and spell out the implications for rates, FX and equities
Review model-generated analyses and grade them against your own standard
Who we are looking for
A former economist or adviser from the relevant central bank, or a senior local rates or FX strategist who covered it through multiple policy cycles
Professional fluency in the source language
Deep knowledge of that bank's reaction function and communication style, and experience reading it in real time
Typically 8+ years of direct experience, or unusually strong evidence of equivalent performance
Backgrounds we look at first: the exact central bank, the BIS, the IMF, leading local institutions, top emerging-markets teams at global banks, and established macro funds. Brand-name experience is a strong first-pass signal but is not a hard requirement — direct experience and performance on the work sample determine who qualifies.
Point-in-time discipline
Every task is graded on reasoning from the stated cutoff without hindsight, data leakage, confidential information, or material non-public information.
Contractor· Remote
Status: Open
Expert WorkMercor
About the work
We are building expert-authored forecasting and research data used to evaluate and improve AI models on real financial analysis. Each task asks a practitioner to reason from a fixed evidence cutoff — no hindsight — and document the judgment a strong analyst would have made at that moment.
This role covers company event propagation: identifying the companies related to an upcoming event and estimating how the catalyst should transmit to each of them.
What you will do
Map suppliers, customers, competitors, distributors, substitutes and geographic exposure from EDGAR filings, footnotes, exhibits, transcripts and industry data
Identify related companies ahead of an event and separate direct exposure from weak thematic correlation
Estimate direction, magnitude, horizon and confidence, and name the revenue, margin, earnings or valuation mechanism behind each
Review model-generated analyses and grade them against your own standard
Who we are looking for
A senior sector PM, lead equity analyst, or event-driven investor with deep knowledge of a specific industry
Hands-on experience mapping a company's economic network from primary filings, not from screens or third-party tags
Typically 8+ years of direct experience, or unusually strong evidence of equivalent performance
Backgrounds we look at first: top multi-manager and event-driven funds, leading sector teams at major asset managers and banks, and elite specialist research firms — for example Citadel, Millennium, Point72, Balyasny, D. E. Shaw, and top sell-side sector franchises. Brand-name experience is a strong first-pass signal but is not a hard requirement — direct experience and performance on the work sample determine who qualifies.
Point-in-time discipline
Every task is graded on reasoning from the stated cutoff without hindsight, data leakage, confidential information, or material non-public information.
Contractor· Remote
Status: Open
ResearchMercor
About the work
We are building expert-authored forecasting and research data used to evaluate and improve AI models on real financial analysis. Each task asks a practitioner to reason from a fixed evidence cutoff — no hindsight — and document the judgment a strong analyst would have made at that moment.
This role covers single-name equity analyst publications: predicting when a named sell-side analyst will publish after a catalyst, and what that update will contain.
What you will do
Forecast the timing and content of a named analyst's post-catalyst research note
Reason from filings, earnings, transcripts, estimates, valuation and ratings to an expected published view
Document the internal research workflow that determines how and when an equity research report gets produced
Review model-generated analyses and grade them against your own standard
Who we are looking for
A former lead sell-side equity analyst or highly senior research associate who personally published post-catalyst research in the exact sector
Deep command of filings, earnings, transcripts, estimates, valuation, ratings, and the internal workflow behind an equity research report
Typically 8+ years of direct experience, or unusually strong evidence of equivalent performance
Backgrounds we look at first: Institutional Investor-ranked teams and leading research franchises such as Goldman Sachs, Morgan Stanley, JPMorgan, Bank of America, Citi, UBS, Barclays, Bernstein, Jefferies and Wolfe Research. Former colleagues, direct coverage rivals, and senior buy-side consumers of a named analyst's work are especially valuable. Brand-name experience is a strong first-pass signal but is not a hard requirement — direct experience and performance on the work sample determine who qualifies.
Point-in-time discipline
Every task is graded on reasoning from the stated cutoff without hindsight, data leakage, confidential information, or material non-public information.
Contractor· Remote
Status: Open
Expert WorkMercor
Mercor is partnering with a biotech and pharma research team on expert human-evaluation work — creating and critiquing rubrics that analyze commercial drugs and drug-development programs. We're seeking a disease-area clinician for a paid pilot, with the potential to continue as the work scales.
Responsibilities
Create and critique rubrics that analyze commercial drugs and drug-development programs
Interpret clinical trial endpoints and judge whether results would change prescribing
Assess what that means for real-world uptake in your therapeutic area
Apply this across the pilot's set of drugs and programs
Requirements
US-based disease-area clinician (practising physician, MD/DO)
Familiarity with biotech/pharma development programs
Deep expertise in a specific therapeutic area
Board-certified and actively practising in your specialty
Engagement Details
Duration: Approximately 10–20 hours over a 1–2 week pilot
Remote — US-based
Why Participate
Help improve expert AI evaluation of drugs and drug-development programs
Recurring engagement for strong contributors
Part-time· Remote — US-based or deep US-market experience
Status: Open
Expert WorkMercor
Mercor is partnering with a biotech and pharma research team on expert human-evaluation work — creating and critiquing rubrics that analyze commercial drugs and drug-development programs. We're seeking a pharma commercial / forecasting expert for a paid pilot, with the potential to continue as the work scales.
Responsibilities
Create and critique rubrics that analyze commercial drugs and drug-development programs
Build or critique a launch curve (uptake, peak share, trajectory)
Judge whether a commercial forecast's assumptions (analogs, ramp, peak, loss of exclusivity) are defensible
Apply this across the pilot's set of drug launches
Requirements
US-based pharma commercial / forecasting professional (people from pharma sales teams can work here too)
Familiarity with biotech/pharma development programs
Experience building or critiquing drug launch / uptake models
5+ years in pharma commercial forecasting, analytics, or strategy
Engagement Details
Duration: Approximately 10–20 hours over a 1–2 week pilot
Remote — US-based
Why Participate
Help improve expert AI evaluation of drugs and drug-development programs
Recurring engagement for strong contributors
Part-time· Remote — US-based or deep US-market experience (United States)
Status: Open
Expert WorkMercor
Mercor is partnering with a biotech and pharma research team on expert human-evaluation work — creating and critiquing rubrics that analyze commercial drugs and drug-development programs. We're seeking a biotech investment analyst (specialist-fund background) for a paid pilot, with the potential to continue as the work scales.
Responsibilities
Create and critique rubrics that analyze commercial drugs and drug-development programs
Provide overall company and asset assessment — mechanism, clinical data, competitive position, and value drivers
Judge the quality of an investment-style thesis and flag weak, overconfident, or missing assumptions
Apply your assessment across the pilot's set of companies (~5–10)
Requirements
US-based biotech / healthcare investment analyst with a specialist-fund background
Familiarity with biotech/pharma development programs
Able to assess a drug asset and the company behind it end-to-end
5+ years evaluating biotech/pharma companies or assets
Engagement Details
Duration: Approximately 10–20 hours over a 1–2 week pilot
Remote — US-based
Why Participate
Help improve expert AI evaluation of drugs and drug-development programs
Recurring engagement for strong contributors
Part-time· Remote — US-based or deep US-market experience
Status: Open
Expert WorkMercor
Mercor's People team is building its compensation and equity foundation from scratch. We want to think it through with people who have done it before.
We're looking for Total Rewards practitioners with depth in one or both of the following. Either one on its own is enough.
Compensation design & architecture
Built salary bands, leveling frameworks, and job architecture from the ground up
Owned an annual compensation cycle: merit planning, promotion decisions, bonus programs, equity refresh
Benchmarked against a peer set you then had to defend to a skeptical exec team
Designed incentive structures that were simple, credible, and changed behavior
Equity program management
Designed option and RSU programs: grant guidelines, pool planning, vesting structures, refresh philosophy
Worked through 409A valuations, plan governance, and grant administration at a venture-backed company
Built the modeling and communication that lets candidates and employees understand what their equity is worth
Those two are what we screen on. Nothing below is required. If you have the whole Total Rewards picture, say so.
Also valuable
Compensation philosophy, benchmarking methodology, pay equity and pay transparency
Compensation design for a global or contractor workforce at scale
Benefits program design, HRIS and compensation tooling
Executive compensation, plan governance, or equity through IPO readiness
Context
Mercor is a Series C company at a $10B valuation, scaling from roughly 500 employees, with a large global contractor network alongside a growing full-time workforce. Nothing is settled yet: what the compensation philosophy should be, how levels map across very different functions, how equity gets granted and explained.
How this works
Applying starts with a short screen. If your background fits, we'll invite you to a paid conversation about a live question we're facing. You're paid for it whether or not anything follows.
Rate is $50–$200/hr depending on depth of experience. Engagements run a few hours at a time, scoped to one question.
We review every submission.
Contractor· Remote
Status: Open
Expert WorkMercor
About the work
We are building expert-authored forecasting and research data used to evaluate and improve AI models on real political and financial analysis. Each task asks a practitioner to reason from a fixed evidence cutoff — no hindsight — and document the judgment a strong analyst would have made at that moment.
This role covers political report authorship: elections, polling, and political-risk events.
What you will do
Author point-in-time political reports and forecasts from a stated evidence cutoff
Make and document directional judgments about polling, win probabilities, and market-implied odds
Explain the causal mechanism behind an event's expected political and market impact
Review model-generated analyses and grade them against your own standard
Who we are looking for
Local political analysts with hands-on experience on specific races in swing states: current or upcoming Senate, governor, or statewide contests, or recent cycles in the same state
On-the-ground knowledge of the electorate, the candidates, and the local political environment, from roles such as university political scientist, state or regional pollster, state-level campaign or party analytics staff, or state political-risk analyst
A record of making live judgments about polling, win probabilities, or odds in those races — not retrospective commentary
Strong polling literacy and causal event analysis
Typically 8+ years of direct experience, or unusually strong evidence of equivalent performance
Backgrounds we look at first: political science departments and survey research centers at universities in the target states, state and regional pollsters, state-level campaign and party analytics teams, and decision desks or race-ratings outlets with state-specific coverage. National forecasting or political-risk experience is welcome when paired with deep knowledge of a specific state. Brand-name experience is a strong first-pass signal but is not a hard requirement — direct experience and performance on the work sample determine who qualifies.
Not a fit
Profiles whose experience is mainly international politics, geopolitics, or country risk, with little or no work on US races
Analysts who have not worked on a current or recent US race in the state they would cover
Pure communications or journalism profiles without demonstrated forecasting, polling, or probabilistic judgment
Academic profiles whose work is purely theoretical, with no analysis of live races
Point-in-time discipline
Every task is graded on reasoning from the stated cutoff without hindsight, data leakage, confidential information, or material non-public information.
Contractor· Remote (Canada and United States)
Status: Open
Expert WorkMercor
About the work
We are building expert-authored forecasting and research data used to evaluate and improve AI models on real political and financial analysis. Each task asks a practitioner to reason from a fixed evidence cutoff — no hindsight — and document the judgment a strong analyst would have made at that moment.
This role covers political report authorship: elections, polling, and political-risk events.
What you will do
Author point-in-time political reports and forecasts from a stated evidence cutoff
Make and document directional judgments about polling, win probabilities, and market-implied odds
Explain the causal mechanism behind an event's expected political and market impact
Review model-generated analyses and grade them against your own standard
Who we are looking for
Local political analysts with hands-on experience on specific races in swing states: current or upcoming Senate, governor, or statewide contests, or recent cycles in the same state
On-the-ground knowledge of the electorate, the candidates, and the local political environment, from roles such as university political scientist, state or regional pollster, state-level campaign or party analytics staff, or state political-risk analyst
A record of making live judgments about polling, win probabilities, or odds in those races — not retrospective commentary
Strong polling literacy and causal event analysis
Typically 8+ years of direct experience, or unusually strong evidence of equivalent performance
Backgrounds we look at first: political science departments and survey research centers at universities in the target states, state and regional pollsters, state-level campaign and party analytics teams, and decision desks or race-ratings outlets with state-specific coverage. National forecasting or political-risk experience is welcome when paired with deep knowledge of a specific state. Brand-name experience is a strong first-pass signal but is not a hard requirement — direct experience and performance on the work sample determine who qualifies.
Not a fit
Profiles whose experience is mainly international politics, geopolitics, or country risk, with little or no work on US races
Analysts who have not worked on a current or recent US race in the state they would cover
Pure communications or journalism profiles without demonstrated forecasting, polling, or probabilistic judgment
Academic profiles whose work is purely theoretical, with no analysis of live races
Point-in-time discipline
Every task is graded on reasoning from the stated cutoff without hindsight, data leakage, confidential information, or material non-public information.
Contractor· Remote (Canada and United States)
Status: Open
Expert WorkMercor
About the work
We are building expert-authored forecasting and research data used to evaluate and improve AI models on real political and financial analysis. Each task asks a practitioner to reason from a fixed evidence cutoff — no hindsight — and document the judgment a strong analyst would have made at that moment.
This role covers political report authorship: elections, polling, and political-risk events.
What you will do
Author point-in-time political reports and forecasts from a stated evidence cutoff
Make and document directional judgments about polling, win probabilities, and market-implied odds
Explain the causal mechanism behind an event's expected political and market impact
Review model-generated analyses and grade them against your own standard
Who we are looking for
Local political analysts with hands-on experience on specific races in swing states: current or upcoming Senate, governor, or statewide contests, or recent cycles in the same state
On-the-ground knowledge of the electorate, the candidates, and the local political environment, from roles such as university political scientist, state or regional pollster, state-level campaign or party analytics staff, or state political-risk analyst
A record of making live judgments about polling, win probabilities, or odds in those races — not retrospective commentary
Strong polling literacy and causal event analysis
Typically 8+ years of direct experience, or unusually strong evidence of equivalent performance
Backgrounds we look at first: political science departments and survey research centers at universities in the target states, state and regional pollsters, state-level campaign and party analytics teams, and decision desks or race-ratings outlets with state-specific coverage. National forecasting or political-risk experience is welcome when paired with deep knowledge of a specific state. Brand-name experience is a strong first-pass signal but is not a hard requirement — direct experience and performance on the work sample determine who qualifies.
Not a fit
Profiles whose experience is mainly international politics, geopolitics, or country risk, with little or no work on US races
Analysts who have not worked on a current or recent US race in the state they would cover
Pure communications or journalism profiles without demonstrated forecasting, polling, or probabilistic judgment
Academic profiles whose work is purely theoretical, with no analysis of live races
Point-in-time discipline
Every task is graded on reasoning from the stated cutoff without hindsight, data leakage, confidential information, or material non-public information.
Contractor· Remote (Canada and United States)
Status: Open
Expert WorkMercor
Mercor is partnering with a biotech and pharma research team on expert human-evaluation work — creating and critiquing rubrics that analyze commercial drugs and drug-development programs. We're seeking a payer / market access expert for a paid pilot, with the potential to continue as the work scales.
Responsibilities
Create and critique rubrics that analyze commercial drugs and drug-development programs
Set and pressure-test gross-to-net and formulary-tier assumptions by drug class
Judge whether coverage, rebating, and tiering assumptions reflect how payers actually behave
Apply this across the pilot's set of drugs and drug classes
Requirements
US-based payer / market access professional
Familiarity with biotech/pharma development programs
Hands-on with gross-to-net, rebates, and formulary tiering by drug class
5+ years in market access, pricing & reimbursement, or managed markets
Engagement Details
Duration: Approximately 10–20 hours over a 1–2 week pilot
Remote — US-based
Why Participate
Help improve expert AI evaluation of drugs and drug-development programs
Recurring engagement for strong contributors
Part-time· Remote — US-based or deep US-market experience
Status: Open
Expert WorkMercor
About the work
We are building expert-authored forecasting and research data used to evaluate and improve AI models on real political and financial analysis. Each task asks a practitioner to reason from a fixed evidence cutoff — no hindsight — and document the judgment a strong analyst would have made at that moment.
This role covers political report authorship: elections, polling, and political-risk events.
What you will do
Author point-in-time political reports and forecasts from a stated evidence cutoff
Make and document directional judgments about polling, win probabilities, and market-implied odds
Explain the causal mechanism behind an event's expected political and market impact
Review model-generated analyses and grade them against your own standard
Who we are looking for
A senior elections forecaster, campaign strategist, polling or statistical-methodology expert, or political-risk analyst
A record of making live judgments about polling, win probabilities, or odds — not retrospective commentary
Strong polling literacy and causal event analysis
Typically 8+ years of direct experience, or unusually strong evidence of equivalent performance
Backgrounds we look at first: top national polling and election-forecasting organizations, major decision desks, senior analytics teams from presidential, Senate or governor races, and political-risk desks at leading banks, funds, or firms such as Eurasia Group and EIU. Brand-name experience is a strong first-pass signal but is not a hard requirement — direct experience and performance on the work sample determine who qualifies.
Not a fit
Pure communications, journalism, or academic profiles without demonstrated forecasting, polling, or probabilistic judgment.
Point-in-time discipline
Every task is graded on reasoning from the stated cutoff without hindsight, data leakage, confidential information, or material non-public information.
Contractor· Remote
Status: Open
ResearchMercor
Mercor is recruiting Senior Economics Research Experts for a research project with a leading foundational model AI lab.
You are a great fit if you:
Have at least 2 years of experience working for top institutions, leading economics research (e.g. World Bank, IMF, Fed, Graduate Schools)
PhD in Economics
Here are more details about the role:
You must be able to commit at least 10 hours per week for this role
This is a minimum four week engagement
Successful contributions increase the odds that you are selected on future projects with Mercor
Contractor· Remote
Status: Open
Expert WorkMercor
About the Role
Mercor is hiring practicing Primary Care Physicians (MD) on behalf of a healthcare AI partner building advanced clinical documentation and decision-support tools. In this role you will apply your day-to-day outpatient expertise to review, annotate, and evaluate clinical documentation, directly shaping the accuracy, safety, and clinical usefulness of medical AI systems.
This role is designed for clinicians who are currently practicing primary care, family medicine, or general internal medicine and who write outpatient clinical notes as part of their regular work.
This is a multilingual cohort. In addition to English, you must be able to speak, listen, and write in at least one other language at an advanced (C1) level or above.
Key Responsibilities
Clinical Documentation Review
Review outpatient clinical notes, encounter summaries, and EHR documentation for accuracy, completeness, and clinical soundness
Evaluate AI-generated notes and summaries against what a practicing PCP would actually document
Annotation & Structured Feedback
Annotate outpatient encounter data against detailed guidelines
Flag omissions, hallucinations, clinical inaccuracies, and documentation gaps in AI-generated output
Provide structured, written feedback that engineering and product teams can act on
Knowledge Contribution
Contribute expert input on annotation guidelines, documentation standards, and edge-case definitions
Raise clarifying questions where guidance is ambiguous and help refine the guidelines
Required Qualifications
MD, with 2+ years post-residency, currently practicing primary care / family medicine / general internal medicine
US-based
Direct experience writing clinical notes in an outpatient setting
In addition to English, advanced (C1 or above) proficiency — speaking, listening, and writing — in at least one of the following languages:
Spanish · Chinese (Mandarin) · Chinese (Cantonese) · Tagalog · Russian · Haitian Creole
Korean · Arabic · Portuguese · Polish · Japanese
Turkish · Italian · Ukrainian · Romanian · Finnish · French · Danish · Catalan · Hungarian · Czech · German · Bulgarian · Indonesian · Dutch
Minimum availability of 10 hours/week
Preferred Qualifications
5+ years of experience post-residency
Familiarity with Epic
Experience with clinical documentation quality review, note auditing, or CDI exposure
Prior AI/ML annotation or model evaluation work experience, with strong performance reviews
Experience documenting patient care in a language other than English
Work Arrangement
Remote, part-time — minimum 10 hours/week
Flexible scheduling, designed around an active clinical practice
Contractor· Remote (United States)
Status: Open
CodingMercor
About the work
Mercor is designing a benchmark that measures how well AI agents do real enterprise cyber defense work. Before we build it, we want to hear from people who do that work every day.
This is a short paid research engagement, not a task or data project. You will join two to three one-hour video conversations with the Mercor team over roughly four weeks, scheduled around your availability.
What we will talk about
How your work actually happens: the tools you live in, what lands in your queue, where judgment matters and where it does not.
How your team measures whether a triage, investigation, containment, hunt, detection rule or patch was done well.
Where AI assistance helps you today, where it gets in the way, and what would make a benchmark of AI on this work credible to you.
Our draft task taxonomy: what is missing, what is mislabeled, what you would weight differently.
Who we are looking for
Current or recent hands-on practitioners in enterprise security, for example:
SOC analysts and SOC leads (tier 2 and above)
Incident responders and digital forensics investigators
Detection engineers and threat hunters
Application security or product security engineers who find and fix vulnerabilities in production code
Security engineers who have run or been on the receiving end of a red team engagement
Experience with an EDR and SIEM stack (CrowdStrike Falcon, Microsoft Defender and Sentinel, Splunk, SentinelOne, Elastic or similar) is a plus. Security leaders are welcome if you are still close to the work.
Pay and time
Paid hourly for interview time as a spot bonus. Sessions are one hour; no prep is expected.
Two to three sessions in total. Nothing to build, label or submit.
Remote, US-based.
Confidentiality
We will ask you to describe patterns, not specific incidents, and to leave out anything confidential about current or former employers or customers. Your input is used only to design the benchmark and is never attributed to you or your employer.
Contractor· United States (remote) (United States)
Status: Open
Expert WorkMercor
Mercor is partnering with a biotech and pharma research team on expert human-evaluation work — creating and critiquing rubrics that analyze commercial drugs and drug-development programs. We're seeking an epidemiologist for a paid pilot, with the potential to continue as the work scales.
Responsibilities
Create and critique rubrics that analyze commercial drugs and drug-development programs
Size the patient population for a given drug or indication (prevalence, incidence, diagnosed → treated → addressable)
Judge whether a patient-population estimate is sound and well-sourced, and flag over- or under-counting
Apply this across the pilot's set of drugs and indications
Requirements
US-based epidemiologist
Familiarity with biotech/pharma development programs
Experience turning real-world data (claims, EHR, registries) into patient funnels
5+ years practising epidemiology (graduate degree in epidemiology, biostatistics, or public health)
Engagement Details
Duration: Approximately 10–20 hours over a 1–2 week pilot
Remote — US-based
Why Participate
Help improve expert AI evaluation of drugs and drug-development programs
Recurring engagement for strong contributors
Part-time· Remote — US-based or deep US-market experience
Status: Open
ResearchMercor
Mercor is conducting a paid research study in collaboration with a leading AI research lab focused on improving healthcare. We are seeking board-certified urologists and medical oncologists in the United States who manage patients with metastatic prostate cancer to take part in a short online survey about treatment decision-making.
Responsibilities
Participants will be asked to:
Complete a structured ~30-minute online survey
Share perspectives on how you evaluate and select systemic treatments for patients with prostate cancer
Submit all responses within the given timeline
Requirements
Urologist or medical oncologist with an MD or DO
Board certified in your specialty
Hold an active, unrestricted US medical license and practice primarily in the United States
Spend at least 25% of your professional time in direct patient care
Have cared for prostate-cancer patients in the past 12 months, including at least one patient with metastatic hormone-sensitive (mHSPC) or castration-resistant (mCRPC) prostate cancer
Regularly manage metastatic prostate cancer, with primary or shared responsibility for selecting systemic treatment
Able to independently complete a ~30-minute online survey
Please note: this study is not open to anyone who has taken part in prostate-cancer market research in the past 3 months, or who (or whose immediate family) works for a pharmaceutical, diagnostics, market research, or advertising company, a wholesaler, or a specialty pharmacy.
Engagement Details
Format: Online survey
Duration: Approximately 30 minutes
Compensation: One-time payment upon successful verification of the submission
Location: Remote (United States)
Why Participate
Contribute to research shaping the next generation of healthcare AI tools
Share your real-world clinical expertise in managing advanced prostate cancer
Task-based· Remote (United States) (United States)
Status: Open
Expert WorkMercor
About the Role
Mercor is hiring practicing Inpatient Hospitalists (MD) on behalf of a healthcare AI partner building advanced clinical documentation and decision-support tools. In this role you will apply your active inpatient expertise to review, annotate, and evaluate hospital clinical documentation, directly shaping the accuracy, safety, and clinical usefulness of medical AI systems.
This role is designed for physicians with a current inpatient practice who write and read hospital documentation as part of their regular work.
This is a multilingual cohort. In addition to English, you must be able to speak, listen, and write in at least one other language at an advanced (C1) level or above.
Key Responsibilities
Clinical Documentation Review
Review inpatient documentation — H&Ps, daily progress notes, and discharge summaries — for accuracy, completeness, and clinical soundness
Evaluate AI-generated inpatient notes and summaries against what a practicing hospitalist would actually document
Annotation & Structured Feedback
Annotate inpatient encounter data against detailed guidelines
Flag omissions, hallucinations, clinical inaccuracies, and documentation gaps in AI-generated output
Provide structured, written feedback that engineering and product teams can act on
Knowledge Contribution
Contribute expert input on annotation guidelines, documentation standards, and edge-case definitions
Raise clarifying questions where guidance is ambiguous and help refine the guidelines
Required Qualifications
MD — hospitalist or internal medicine — with 2+ years post-residency and a current inpatient practice
US-based
Hands-on experience writing and reading at least one of the following: H&Ps, progress notes, discharge summaries
In addition to English, advanced (C1 or above) proficiency — speaking, listening, and writing — in at least one of the following languages:
Spanish · Chinese (Mandarin) · Chinese (Cantonese) · Tagalog · Russian · Haitian Creole
Korean · Arabic · Portuguese · Polish · Japanese
Turkish · Italian · Ukrainian · Romanian · Finnish · French · Danish · Catalan · Hungarian · Czech · German · Bulgarian · Indonesian · Dutch
Minimum availability of 10 hours/week
Preferred Qualifications
5+ years of experience post-residency
Familiarity with Epic
Prior AI/ML annotation or model evaluation work experience, with strong performance reviews
Experience documenting patient care in a language other than English
Work Arrangement
Remote, part-time — minimum 10 hours/week
Flexible scheduling, designed around an active clinical practice
Contractor· Remote (United States)
Status: Open