Member of Technical Staff, Data Analysis and Evaluation
Cohere · London
Who are we? 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 co-headquartered in Toronto and San Francisco, with key offices in London, New York City, Montreal, Seoul, Germany and Paris. Join us! Why this role? As a Member of Technical Staff in Data Analysis and Evaluation, you will play a pivotal role in ensuring the quality, reliability, and performance of our large language models (LLMs). Your primary focus will be on designing and conducting data collection tasks, assessing and evaluating dataset quality, and analysing the robustness and generalisability of our models. You will work closely with cross-functional teams, including researchers, engineers, and data annotators, to conduct data-driven decision-making and improve the overall effectiveness of our AI systems. This role combines expertise in statistics, experimental design incl. human annotators, and machine learning to ensure that our models are trained on high-quality data and perform reliably across diverse scenarios. You will contribute to Cohere’s mission of advancing AI by ensuring our systems are robust, scalable, and impactful. Please Note: We have offices in London, Paris, Toronto, San Francisco, and New York, but we also embrace being remote-friendly! There are no restrictions on where you can be located for this role. As a Mem