Senior Member of Technical Staff, Safety and Security for Agents

Cohere is a security-first enterprise AI company building foundation AI models and end-to-end products. As a Member of Technical Staff in the Safety for Agents team, you will make a meaningful impact on the development of better, fairer, more trustworthy, and more secure Large Language Models (LLMs). The role focuses on data generation, post-training algorithms, and evaluation methods to ensure Safety in the next generation of models that can access external resources and take actions in the world.

Responsibilities

Make a meaningful impact on the development of better, fairer, more trustworthy, and more secure Large Language Models (LLMs); Focus on data generation, post-training algorithms, and evaluation methods to ensure Safety in the next generation of models that can access external resources and take actions in the world; Work closely with cross-functional machine learning teams and data annotation teams; Collaborate with product and policy teams; Combine expertise in machine learning, ethical and responsible AI, experimental design, and data generation and management; Tackle totally new scientific problems, implement pieces needed to test solutions, and dive into messy data and results; Be on a small team with autonomy and decision-making power, responsible for making the next generation of LLMs better for society as a whole

Requirements

Strong statistical skills and experience evaluating scientific experiments related to data collection and model performance; Extremely strong software engineering skills; Strong expertise in designing and conducting data collection tasks, including working with human annotators; 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 generalizability 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)

Benefits

Weekly lunch stipend of $75/£75 or equivalent in local currency; Full health and dental benefits, including separate budget for mental health; RRSP matching, 401K, Pension Scheme; 100% Parental Leave top-up for up to 6 months, for either parent; Annual enrichment benefits including arts & culture, fitness/wellness, quality time, workspace improvement credit, and education & learning stipend; 6 weeks of paid vacation (30 working days); Budget for traveling to other offices if remote, plus annual company offsite; Co-working benefit for those not near an office; $500 home office stipend; For those in office: daily lunch program, snacks, and regular community and social events