Cohere - Member of Technical Staff
Requirements
• You may be a good fit if: • You have engineered agents and optimized them for specific industry use cases • You have spent dozens of hours reviewing agent trajectories to pinpoint exact failure points and fix them with model training or harness engineering • You obsess over measuring agentic capabilities and turning that into a repeatable process • You have had many debates about what a good outcome from an AI agent should look like, you translated that into verifier implementations and tuned the reward designs • You have designed and run annotation workflows to surface insights into agent performance and verify data quality • You have built synthetic data pipelines to scale eval and training efforts • You use agents yourself in your daily work, and have stories about how you improved your setup to 10x your productivity • A plus: you have experience with training with RL: scaling, troubleshooting and tuning the environments • If some of the above doesn’t line up perfectly with your experience, we still encourage you to apply. • Working Location:This role can be based remotely or from one of our office locations listed on the job description - there is no minimum in-office qualification requirement. We care most about hiring exceptional people regardless of locations, though please check the location listed on the posting for guidance around the core time zone or working hours alignment expected for the role. • Working Location: • Full-Time Employees at Cohere enjoy these Perks: • A weekly lunch stipend of $75/£75 or equivalent in your local currency for lunch. • Full health and dental benefits, including a separate budget for mental health. • RRSP matching, 401K, Pension Scheme. • 100% Parental Leave top-up for up to 6 months, for either parent.
Responsibilities
• There are many open problems in this space. As a Member of Technical Staff, RL Environments, you will: • Build new RL environments targeting different agentic capabilities and industry areas • Train and evaluate agents in those environments • Make all the pieces work together: tasks, data, tool implementations, and verifiers • Work across modeling and product to identify gaps in agent performance, and improve both the agents and the environments • Work with external vendors to create high-quality, expert-built RL environments, and build tools to ensure high task, data, and verifier quality • Automate the discovery of model capability gaps, and systematically measure agent performance during evals and training
Benefits
• Canada - Toronto (GTA), MontrealBase Salary CA$295K – CA$535K • Offers Equity • CanadaBase Salary CA$250K – CA$460K • Offers Equity • USA - California, New York and WashingtonBase Salary $205K – $380K • Offers Equity • USA - All Other StatesBase Salary $175K – $325K • Offers Equity • Arts & culture, fitness/wellness, quality time, and a workspace improvement credit. • Education & learning stipend for conferences, courses, and coaching. • 6 weeks of paid vacation (30 working days!) • Budget for traveling to other offices if you are remote, plus an annual company offsite. • How and Where We Work: • Cohere is remote-friendly, but we also have offices in Toronto, London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul with more opening soon. • For those in the office: a daily lunch program, plenty of snacks, and regular community and social events. • For those not near an office: a co-working benefit so you can work alongside others in your city. • Everyone receives a $500 home office stipend to set up your workspace properly. • If any of the above doesn’t line up exactly with your experience, we still encourage you to apply. • We strive to create an inclusive work environment for all; we welcome applicants from all backgrounds and are committed to providing equal opportunities. Should you require any accommodations during the recruitment process, please submit an Accommodations Request Form, and we will work together to meet your needs. • We may use AI-enabled tools to screen and assess applicants against the criteria for this position. This helps our recruiters identify potentially qualified candidates, but it doesn't limit the applications our recruiters may review or consider.
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