Member of Technical Staff, Research Engineering | $7-$8/hr Remote
Overview
This role places you at the cutting edge of Reinforcement Learning, where you'll build novel training environments, scalable pipelines, and robust evaluation frameworks that push the boundaries of AI. You'll bridge the gap between research and production, turning experimental concepts into high-performance systems that power real-world applications. As a key member of the research engineering team, you'll own the full lifecycle of RL system development, from environment design to model fine-tuning.
What You'll Do6
- 1Design and build self-contained RL environments that simulate complex real-world tasks, including custom reward functions, verifiers, and evaluation logic.
- 2Create and scale training pipelines and multi-component processes (MCPs) that support reproducible, large-scale experimentation.
- 3Develop automated data generation pipelines that leverage synthetic data to accelerate training cycles without sacrificing quality.
- 4Construct AI-driven evaluation and quality assurance systems that handle automated grading, validation, and continuous feedback loops.
- 5Fine-tune and optimize open-source RL models using internally generated datasets and custom training strategies to improve performance.
- 6Establish benchmarking frameworks to systematically measure model capability, robustness, and data quality across diverse tasks.
Requirements6
- 1Deep hands-on experience with Reinforcement Learning, including environment design and understanding training dynamics.
- 2Proven track record of building and scaling RL systems, training pipelines, or experimentation frameworks from scratch.
- 3Strong skills in automation and data generation, particularly with synthetic data pipelines for ML training.
- 4Familiarity with automated evaluation systems, model validation workflows, and quality assurance tools.
- 5Experience fine-tuning and evaluating open-source ML models using custom datasets and training strategies.
- 6Excellent technical writing and communication skills to document and share research findings clearly.
Who Should Apply
You're a hands-on engineer with a passion for advancing AI through Reinforcement Learning — you thrive at the intersection of research and engineering. You enjoy building complex systems, experimenting with new ideas, and scaling them to production. You're comfortable working autonomously in a fast-paced, collaborative environment and have a knack for turning experimental concepts into reliable, high-performance code. If you're excited about pushing the capabilities of modern AI models, this role is for you.
Salary Insight
The national base salary range for this full-time position is $140,000 – $180,000 USD, plus eligibility for equity compensation, performance-based bonuses, and a comprehensive benefits package including up to 100% health insurance premium reimbursement, paid time off, and a 401(K) plan with company match.
Required Skills
Application Tip
Highlight specific RL projects you've built from scratch — include links to environments, training pipelines, or evaluation frameworks you've developed. Showcasing your ability to both design experiments and ship production-ready code will set you apart.
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