Research

Member of Technical Staff, Research Engineering

Status: Open

Micro1

Pay
$180,000–$240,000/yr
Location
Remote
Employment type
Full-time
Openings
1
Posted
2026-06-22

About this opportunity

Job Title: Member of Technical Staff, Research Engineering Job Type: Full-time Location: Remote The Role We are seeking a Research Engineer to operate at the frontier of Reinforcement Learning (RL), developing novel environments, training pipelines, and evaluation systems that advance the capabilities of modern AI models. This role sits at the intersection of research and production, translating experimental ideas into scalable, high-performance systems. What You’ll Work On - Architect self-contained RL environments that capture complex, real-world tasks, including reward functions, verifiers, and evaluation logic. - Design and scale episode pipelines and multi-component training processes (MCPs) to support reproducible experimentation. - Build automated data generation systems, leveraging synthetic data to accelerate training cycles without compromising quality. - Develop and integrate AI-driven evaluation and quality assurance systems for automated grading, validation, and feedback loops. - Fine-tune and optimize open-source RL models using internally generated datasets and custom training strategies. - Establish benchmarking frameworks to measure model capability, robustness, and data quality across tasks. - Contribute to the release and analysis of evaluations on internal and external benchmark platforms (e.g., micro1 benchmarks). What We're Looking For - Deep experience in Reinforcement Learning, including environment design and training dynamics. - Strong track record of building and scaling RL systems, pipelines, or experimentation frameworks. - Proficient in automation and data generation, including synthetic data pipelines. - Familiar with automated evaluation systems, model validation, and quality assurance workflows. - Experienced in fine-tuning and evaluating open-source ML models. - Clear, concise communicator with strong technical writing skills. - Comfortable operating in fast-paced, research-driven, and highly collaborative environments. Preferred - Experience publishing benchmarks, evaluations, or research artifacts. - Familiarity with evaluation ecosystems (e.g., micro1 benchmarks or similar frameworks). - Background in scalable infrastructure for large-scale RL experimentation. Compensation & Benefits Notice The national pay range for this full-time position is base salary of $180,000 –$240,000 USD. All employees are eligible for equity compensation, and employees may also receive performance-based bonuses, dependent on role and subject to company policies. micro1 provides a comprehensive benefits package, including up to 100% reimbursement for health-insurance premiums, paid time off, a 401(K) plan with a company match, and additional benefits designed to support a high-performing, remote-first workforce. micro1 is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex (including pregnancy, sexual orientation, or gender identity), national origin, age, disability, genetic information, veteran status, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance and/or a reasonable accommodation during the application process, reach out to support@micro1.ai. Our hiring process utilizes artificial intelligence tools to assist in candidate screening and assessment. Our AI tools are designed to complement, not replace, human decision-making. Disclaimer The information contained in this job posting, including but not limited to role responsibilities, qualifications, compensation, and benefits, is provided for informational purposes only and does not constitute a binding offer of employment. micro1 reserves the right to amend, modify, or withdraw any portion of this posting at its sole discretion and without prior notice. All employment decisions are made in accordance with applicable laws and regulations.

Required skills

  • Reinforcement Learning
  • ML-Oriented Data Design
  • RL Environments
  • RL Workflows

What you'll do

  • Architect self-contained RL environments that capture complex, real-world tasks, including reward functions, verifiers, and evaluation logic.
  • Design and scale episode pipelines and multi-component training processes (MCPs) to support reproducible experimentation.
  • Build automated data generation systems, leveraging synthetic data to accelerate training cycles without compromising quality.
  • Develop and integrate AI-driven evaluation and quality assurance systems for automated grading, validation, and feedback loops.
  • Fine-tune and optimize open-source RL models using internally generated datasets and custom training strategies.
  • Establish benchmarking frameworks to measure model capability, robustness, and data quality across tasks.
  • Contribute to the release and analysis of evaluations on internal and external benchmark platforms (e.g., micro1 benchmarks).

Requirements

  • Deep experience in Reinforcement Learning, including environment design and training dynamics.
  • Strong track record of building and scaling RL systems, pipelines, or experimentation frameworks.
  • Proficient in automation and data generation, including synthetic data pipelines.
  • Familiar with automated evaluation systems, model validation, and quality assurance workflows.
  • Experienced in fine-tuning and evaluating open-source ML models.
  • Clear, concise communicator with strong technical writing skills.
  • Comfortable operating in fast-paced, research-driven, and highly collaborative environments.

Preferred qualifications

  • Experience publishing benchmarks, evaluations, or research artifacts.
  • Familiarity with evaluation ecosystems (e.g., micro1 benchmarks or similar frameworks).
  • Background in scalable infrastructure for large-scale RL experimentation.

Compensation

The national pay range for this full-time position is base salary of $180,000 –$240,000 USD. All employees are eligible for equity compensation, and employees may also receive performance-based bonuses, dependent on role and subject to company policies. micro1 provides a comprehensive benefits package, including up to 100% reimbursement for health-insurance premiums, paid time off, a 401(K) plan with a company match, and additional benefits designed to support a high-performing, remote-first workforce.
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$14–$36/hr

Verified Oct 3, 2026

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Job Title: TypeScript + Rust Developer Job Type: Contractor Location: Remote Job Summary: In this role, you'll apply your expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input. No prior experience in AI is required — your domain knowledge is what matters. Key Responsibilities: - Collaborate with cross-functional teams to deliver robust solutions in TypeScript and Rust. - Design, implement, and refactor complex systems, with a focus on codebase migrations or rewrites between language ecosystems. - Create and curate high-quality human data for AI training and evaluation tasks. - Follow best practices for software engineering, including code reviews, testing, and documentation. - Communicate technical concepts clearly via written and verbal communication to both technical and non-technical stakeholders. - Troubleshoot, debug, and optimize codebases in both TypeScript and Rust environments. - Maintain 6+ hours of daily work overlap with the Eastern Time zone to ensure effective collaboration. Required Skills and Qualifications: - 5+ years of professional software development experience, with a proven track record of production-level work. - Idiomatic fluency in TypeScript and Rust, demonstrated through hands-on experience. - Strong background in codebase migrations, rewrites, or working within multiple language environments. - Excellent written and verbal communication skills, with the ability to explain complex technical issues clearly. - Experience producing or working with human-labeled data, ideally for AI or ML applications. - Ability to work independently and as part of a remote, global team. - Fluent English proficiency. Preferred Qualifications: - Previous experience on AI/ML data engineering or data labeling teams. - Contributions to open-source TypeScript or Rust projects. - Background in developing scalable cloud-native applications.

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Verified Oct 3, 2026

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