Member of Technical Staff - RL Environments

Member of Technical Staff - RL Environments; Greater London; Remote; GBP 70,000 - 110,000; Full time

Benefits offered by this job

Weekly lunch stipend

Health and dental benefits

RRSP matching / Pension

Parental Leave top-up

Learning stipend

Vacation (6 weeks)

Home office stipend

Job summary

Cohere is hiring for a role focused on building and evaluating reinforcement learning environments that mirror real enterprise work. You will run AI agents within these environments, optimize both agents and environments, and incorporate feedback from customers to continuously improve the loop.

The position involves collaborating with modeling and product teams to identify gaps, working with external vendors for high-quality environments, and developing tools to ensure data and task quality.

Qualifications

• Engineered agents and optimized them for enterprise RL use cases.
• Reviewed agent trajectories to identify failure points and improve through training or harness engineering.
• Measured agentic capabilities and translated results into verifier implementations and reward designs.
• Designed and ran annotation workflows to surface insights into agent performance and data quality.
• Built synthetic data pipelines to scale evaluation and training workflows.

Responsibilities

• Build new RL environments targeting different agentic capabilities and industry areas.
• Train and evaluate agents in those environments.
• Make all components work together: tasks, data, tool implementations, and verifiers.
• Collaborate with modeling and product teams to identify gaps in agent performance and improve environments.
• Work with external vendors to create high-quality RL environments and build quality assurance tools.
• Automate discovery of model capability gaps and measure performance during evals and training.

Skills

RL environments

Agent training

Experimentation

Verification tools

Synthetic data pipelines

Annotation workflows

Hardware-neutral testing

Daily collaboration

Tools

RL frameworks

Python

Job description

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 headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us!

Role Overview:

Building AI agents that can assist with any kind of enterprise work is a challenging, open-ended problem. One key piece of solving it is replicating real work environments as realistically as possible - filling them with hard tasks to solve, creating plausible input data, and defining clear rewards for completing the work the right way. We build many of these reinforcement learning (RL) environments, then drop our agents into them to evaluate or train them.

In this role, you are responsible for creating these RL environments, running AI agents inside them, and improving both the agents and the environments in the process. The results reach customers, whose feedback feeds back in - and the agent/environment improvement loop continues.

Key Responsibilities:

• 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

Qualifications:

• 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

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.

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.
• Annual enrichment benefits: 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.

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.