Cohere is the innovator of Spectrum Multiplier software for Open Radio Access Networks and existing 4G and 5G mobile networks, and the developer of the Orthogonal Time Frequency Space (OTFS) 6G wireless system. Backed by NEA.
About the role
We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us! Found on 1752vc Careers, the job board for startup and VC roles.
What they're looking for
- Strong software engineering skills
- Experience designing and building large-scale data pipelines for machine learning, ideally for LLM post-training
- Track record of running distributed data processing and model inference at scale
- Good understanding of post-training methods (e.g., SFT, RLHF, DPO) and how data shapes model behaviour
- Excellent communication skills
- This is neither an exhaustive nor necessary set of attributes. Even if none of these apply to you, but you believe you will contribute to Cohere, please reach out. We value diverse backgrounds and perspectives at Cohere
More about this role
Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems.
We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that.
We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft.
We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us!
Role Overview
As a Member of Technical Staff in Post-Training Data Infrastructure, you will build and own the pipelines that produce the post-training data for our large language models (LLMs), from SFT and RL data to synthetic and human-annotated data. You will work closely with researchers and annotation teams so they can iterate on data as quickly as...
Browse similar: Startup jobs