Member of Technical Staff, Data Analysis and Evaluation

Position Overview

• Location Type: Remote
• Job Type: Full-Time
• Salary: Not specified

Cohere's mission is to scale intelligence to serve humanity by training and deploying frontier models for developers and enterprises. We are building AI systems for content generation, semantic search, RAG, and agents, aiming for widespread AI adoption. We are a team of passionate researchers, engineers, designers, and more, each being one of the best in the world at their craft. We value diversity and believe it's a requirement for building great products.

Why this role?

As a Member of Technical Staff in Data Analysis and Evaluation, you will be crucial in ensuring the quality, reliability, and performance of our large language models (LLMs). Your responsibilities will include designing and conducting data collection, assessing dataset quality, and analyzing model robustness and generalisability. You will collaborate with researchers, engineers, and data annotators to drive data-driven decisions and enhance our AI systems. This role requires expertise in statistics, experimental design (including human annotators), and machine learning to ensure high-quality data and reliable model performance.

Responsibilities

• Design and oversee data collection tasks, including supporting human annotators and ensuring data quality.
• Develop and apply statistical methods to evaluate the quality and reliability of datasets.
• Analyze and assess the generalisability and robustness of ML systems across diverse use cases.
• Collaborate with teams to improve dataset quality and model performance.
• Train and fine-tune large language models (LLMs) on distributed training infrastructures.
• Conduct experiments to evaluate model performance and identify areas for improvement.

Requirements

• Extremely strong software engineering skills.
• Strong expertise in designing and conducting data collection tasks, including working with human annotators.
• Strong statistical skills and experience evaluating scientific experiments related to data collection and model performance.
• Experience analyzing datasets with respect to their quality, biases, and suitability for training ML models.
• Hands-on experience training large language models (LLMs) on distributed training infrastructures.
• Familiarity with evaluating and improving the generalisability and robustness of ML systems.
• Proficiency in programming languages such as Python and ML frameworks (e.g., PyTorch, TensorFlow, JAX).
• Excellent communication skills to collaborate effectively with cross-functional teams and present findings.
• One or more papers at top-tier venues (such as NeurIPS, ICML, ICLR, AIStats, MLSys, JMLR, AAAI, Nature, COLING, ACL, EMNLP).

Note: We encourage applications even if not all criteria are met. Diverse backgrounds and perspectives are highly valued.

Company Information

• Company: Cohere
• Mission: To scale intelligence to serve humanity.
• Focus: Training and deploying frontier models for AI systems.
• Values: Obsession with product, hard work, fast pace, customer focus, passion for craft, diversity of perspectives.
• Office Locations: London, Toronto, San Francisco, and New York.
• Work Environment: Remote-friendly.

Application Instructions

Please apply if you are passionate about working hard on a glorious mission with like-minded teammates.