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Cohere

Member of Technical Staff - RL Environments

London
Posted about 23 hours ago
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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:

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

Reasons to use Rodeo

I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?

Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.

Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.

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Grad scheme, placement, apprenticeship? Not sure what you want yet — that's fine. Your agent talks it through with you and turns "I have no idea" into a shortlist.

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Graduate Consultant — 2026 Scheme

PwC·London, UK
£35,000/yr

Why you're a good match

Strong

Your economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.

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It searches the market for you

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Why you're a good match

You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.

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Strong

Experience fit

Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.

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No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.

Qualifications:

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

Note:

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.

If some of the above doesn’t line up perfectly with your experience, we still encourage you to apply.

We value and celebrate diversity and 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.

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.

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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.

Beware of Scams: Cohere will never ask for payment or third-party services (e.g., CV writing) as part of our hiring process. All legitimate roles are listed on the Cohere careers page and LinkedIn only, with all communications from Cohere employees coming from an @cohere.com or @cw.cohere email alias. If jobs are viewed on other sites then please verify these through our official careers page.

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Skills

Reinforcement learning
AI agent engineering
Model training
Synthetic data pipelines
Annotation workflows
Reward design
Verifier implementation
Performance evaluation
Harness engineering
Data quality assurance
Agentic capabilities
Modeling
Product development

Location

London, England, United Kingdom

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