over 1 year ago
Responsibilities
- Design and write high-performance, scalable software for model training
- Post-train models to achieve state-of-the-art performance
- Coordinate with specialist teams such as Agentic and Code to produce broadly capable models
- Develop and implement techniques to improve training-cycle performance across supervised fine-tuning and reinforcement learning
- Research, implement, and experiment with ideas on large-scale compute and data infrastructure
- Contribute to production engineering and research efforts
Requirements
- Extremely strong software engineering skills
- Proficiency in Python and machine learning frameworks such as JAX, PyTorch, and XLA/MLIR
- Experience with distributed training infrastructure including Kubernetes and Slurm, and frameworks such as Ray
- Experience using large-scale distributed training strategies
- Hands-on experience training large models at scale
- Hands-on experience with model post-training, with a strong emphasis on performance optimization
- A paper at a top-tier venue such as NeurIPS, ICML, ICLR, AIStats, MLSys, JMLR, AAAI, Nature, COLING, ACL, or EMNLP is a bonus
Benefits
- Open and inclusive culture and work environment
- Weekly lunch stipend, in-office lunches, and snacks
- Full health and dental benefits, including a separate mental health budget
- 100% parental leave top-up for up to 6 months
- Personal enrichment benefits for arts and culture, fitness and well-being, quality time, and workspace improvement
- Remote-flexible work with offices in Toronto, New York, San Francisco, London, and Paris
- Co-working stipend
- Six weeks of vacation, or 30 working days
Tech Stack
Categories
AI ResearchML Engineering
About Cohere
Cohere builds large language models and an enterprise AI platform that companies use for search, summarization, and workflow automation, delivered via API or private deployments. Founded in 2019 and headquartered in Toronto, it focuses on multilingual models, data controls, and options to run across major clouds or on-premises. The business is privately held and serves security- and compliance-sensitive organizations.