Cohere is looking to scale intelligence to serve humanity by training and deploying frontier models for developers and enterprises. The company aims to build AI systems that power magical experiences like content generation, semantic search, RAG, and agents, and believes its work is instrumental to the widespread adoption of AI.
Requirements
- Proficiency in Python and related ML frameworks such as Tensorflow, TF-Serving, JAX, and XLA/MLIR.
- Experience using large-scale distributed training strategies.
- Familiarity with autoregressive sequence models, such as Transformers.
- Bonus: experience writing kernels for GPUs using CUDA.
- Bonus: experience training on TPUs.
- Bonus: papers at top-tier venues (such as NeurIPS, ICML, ICLR, AIStats, MLSys, JMLR, AAAI, Nature, COLING, ACL, EMNLP).
Responsibilities
- Design, train and improve upon cutting-edge models.
- Help us develop new techniques to train and serve models safer, better, and faster.
- Train extremely large-scale models on massive datasets.
- Explore continual and active learning strategies for streaming data.
- Work closely with product teams to develop solutions.
- Ship state of the art models to production.
- Build elegant training/deployment pipelines.
Other
- Student currently enrolled in a post-secondary program.
- Available for a full-time 3-6 month internship, co-op, or research work term.
- Strong communication and problem-solving skills.
- A demonstrated passion for applied NLP models and products.
- Thoughtful worker, a lifelong learner, and a kind and playful team member.
