Member of Technical Staff, Integration/RL Team (Research Engineer)
Remote • Paris • FullTime
Posted 11mo ago
Remote Work Policy
Fully remote
Employment Type
FullTime
Categories
AI Research Engineer
About the job
Cohere is a leading enterprise AI company focused on building cutting-edge foundation AI models and end-to-end products for real-world business problems. The integration team specifically focuses on developing and scaling machine learning algorithms and infrastructure for LLM post-training, with an emphasis on large-scale, distributed Reinforcement Learning (RL) methods. This role is crucial for enhancing the post-training codebase by implementing new research tools, optimizing algorithms, and scaling distributed RL capabilities. We are looking for passionate individuals who are meticulous in their approach to engineering and science, contributing to both production code and research efforts.
Responsibilities
- Design and write high-performing, scalable software for model training.
- Develop new tools to support and accelerate research and LLM training.
- Coordinate with infrastructure, efficiency, and serving teams, as well as scientific teams, to build an integrated post-training ecosystem.
- Implement techniques to improve performance and speed up training cycles for SFT, offline preference, and RL regimes.
- Research, implement, and experiment with ideas on cluster and data infrastructure.
- Collaborate with scientists, engineers, and other teams.
Requirements
- Extremely strong software engineering skills.
- Proficiency in test-driven development, clean code, and reducing technical debt.
- Proficiency in Python and ML frameworks like JAX, PyTorch, and/or XLA/MLIR.
- Experience with large-scale distributed training strategies, including memory/speed profiling.
- Experience with distributed training infrastructures (e.g., Kubernetes) and frameworks (e.g., Ray) is a bonus.
- Hands-on experience with the post-training phase of model training, focusing on scalability and performance, is a bonus.
- Experience in ML, LLM, and RL academic research is a bonus.
- Deep passion for quality work.
- Enjoy tuning and optimizing large LLM models.
- Comfortable working with individuals of varying software engineering skill levels.
- Comfortable diving into complex ML codebases to identify and resolve issues.
- Ability to thrive in a fast-paced, technically challenging environment.
Benefits
- Weekly lunch stipend ($75/£75 or local equivalent).
- Full health and dental benefits, including a mental health budget.
- RRSP matching, 401K, Pension Scheme.
- 100% Parental Leave top-up for up to 6 months.
- Annual enrichment benefits (arts & culture, fitness/wellness, quality time, workspace improvement).
- Education & learning stipend for conferences, courses, and coaching.
- 6 weeks of paid vacation (30 working days).
- Budget for traveling to other offices (for remote employees).
- Annual company offsite.
- Co-working benefit for those not near an office.
- $500 home office stipend.