Courses and programmes from universities and institutions worldwide.
Member of Technical Staff, Research Engineering
Get alerts for roles like this
More Member of Technical Staff, Research Engineering roles in Remote — straight to your inbox. No account needed.
Applying to this role? Tailor your résumé to this job description in one click, then download it free — just a small ResumeKart footer, no subscription.
Job Description
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 benchmar
Required Skills
Upskill for This Role
Courses from Udemy and edX matched to this role's skills.

Machine Learning: Deep & Reinforcement Learning

Reinforcement Learning Avanzado: DQNs avanzadas

Fundamentals of Reinforcement Learning

Deep Reinforcement Learning Preparation Practice Tests

Artificial Intelligence IV - Reinforcement Learning in Java

Reinforcement Learning (English): Master the Art of RL
ResumeKart may earn a commission from these links at no extra cost to you.
Partner picks for Member of Technical Staff, Research Engineering in Remote
Matched to the skills this page calls for and the candidate's location.
- edXVerified partnerPartner course provider
- UdemyVerified partnerPartner course provider
A marketplace of instructor-created courses across technology, business and creative skills.
- Partner course provider
University and industry courses, professional certificates and online degrees.
Partners are ResumeKart affiliates or institutes it works with; ResumeKart may earn a commission when a candidate enrols. Placement is decided by relevance, not payment. How ResumeKart earns
Prepare to Win This Role
Everything you need to ace the interview and negotiate top-of-band compensation.