Member of Technical Staff, Coding Agent Research & Evaluations

Remotebridge; United States; À distance; USD 200 000 - 260 000; Plein temps

Avantages offerts par ce poste

Equity compensation

Performance-based bonuses

Health-insurance premium reimbursement

401(k) company match

Remote-first workforce

Résumé du poste

micro1 is seeking a Member of Technical Staff to advance evaluation and development of frontier coding agents. You will design benchmarks, methodologies, and data systems shaping how next-generation coding models are measured and improved.

Split across AI research, software engineering, and model evaluation, you will drive end-to-end research, build datasets and protocols, and work with cross-functional teams in a remote-first environment.

Qualifications

• Proven software engineering background with strong Python/C++ skills.
• Experience in ML research, model evaluation, or related disciplines.
• Ability to design and review benchmarks, tasks, and evaluation protocols.
• Strong analytical skills to interpret model behavior and failures.
• Excellent written and verbal communication for diverse audiences.

Responsabilités

• Design and own evaluation frameworks for coding agents, including benchmarks and rubrics.
• Lead end-to-end research initiatives to measure and improve coding model performance.
• Develop datasets, golden examples, and evaluation protocols for reliable assessments.
• Analyze model behavior and failure modes to identify weaknesses and improvements.
• Build tooling and infrastructure for large-scale experiments and data pipelines.
• Establish best practices for coding-agent assessment, ensuring rigor and reproducibility.
• Collaborate with researchers, engineers, and AI teams to design experiments and communicate results.

Connaissances

Python

C++

Software Eng

ML Research

Evaluation Methods

Description du poste

Job Title: Member of Technical Staff, Coding Agent Research & Evaluations

Job Type: Full-time

Location: Remote

The Role

We are seeking a Member of Technical Staff to help advance the evaluation and development of frontier coding agents. Sitting at the intersection of AI research, software engineering, and model evaluation, you will design the benchmarks, methodologies, and data systems that shape how next-generation coding models are measured and improved.

What You'll Do

• Design and own evaluation frameworks for coding agents, including benchmark specifications, scoring methodologies, rubrics, and quality standards.
• Lead end-to-end research initiatives focused on measuring and improving coding model performance across diverse software engineering tasks.
• Develop high-quality datasets, golden examples, and evaluation protocols that enable reliable assessment of frontier coding systems.
• Analyze model behavior and failure modes, identifying systematic weaknesses and translating findings into actionable improvements for training and evaluation.
• Build tooling and infrastructure that support large-scale experimentation, data generation, review workflows, and evaluation pipelines.
• Establish best practices for coding-agent assessment, ensuring methodological rigor, reproducibility, and measurement quality.
• Partner closely with researchers, engineers, and applied AI teams to design experiments and evaluate emerging model capabilities.
• Contribute to technical reports, benchmark studies, and client-facing research initiatives that communicate model performance and insights.

What We're Looking For

• Strong software engineering background with expertise in Python, C++, or comparable programming languages.
• 3+ years of experience in software engineering, machine learning, AI research, evaluation, or related technical disciplines.
• Experience designing, reviewing, or validating technical assessments, benchmarks, coding tasks, or evaluation methodologies.
• Familiarity with large language models, coding agents, reinforcement learning, model evaluation, or related AI systems.
• Proven ability to build tooling, automate workflows, and improve technical processes through systematic experimentation.
• Strong analytical skills with the ability to investigate model behavior and derive insights from complex technical systems.
• Excellent written and verbal communication skills, including the ability to clearly articulate technical findings to diverse audiences.
• Comfortable operating in fast-moving research environments with significant ambiguity and evolving priorities.

Preferred

• Experience working on frontier AI systems, coding agents, or model evaluation research.
• Deep interest in understanding how data, evaluations, and feedback mechanisms influence model capabilities.
• Track record of independently driving ambiguous technical or research projects from conception to execution.
• Experience designing benchmarks or datasets for machine learning systems at scale.
• Familiarity with agentic workflows, tool use, reinforcement learning, or post-training methodologies.
• Publications, open-source contributions, or demonstrated technical leadership in AI, machine learning, or software engineering.

Compensation & Benefits Notice

The national pay range for this full-time position is base salary of $200,000 -$260,000 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 [e-mail].

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.