Member of Technical Staff, Cohere
North Modelling, Evals
More information about location
Enterprise-grade AI solutions for real-world business problems
Be an early applicant
Enterprise-grade AI solutions for real-world business problems
501-1000 employees
Be an early applicant
More information about location
501-1000 employees
Company mission
To empower businesses to scale innovation, boost productivity, and drive progress that reaches everyone.
Role
Who you are
- It is a rigorous applied MLE role for someone who cares deeply about measurement, model behavior, and real-world product quality
- You should be excited by the craft of building careful evals: evals that capture messy agentic workflows, reflect actual customer needs, resist superficial benchmark hacking, and provide useful signal for where the product and models need to go next
- You have improved LLM-powered, agent-powered, or AI-product systems through evals, feedback loops, data curation, prompting, model adaptation, or model selection
- You care deeply about evaluation as a craft: representative tasks, precise rubrics, clean data, failure analysis, regression tracking, and knowing when a metric is giving false confidence
- You have strong applied MLE judgment and can reason clearly about model behavior, eval validity, product outcomes, and production tradeoffs
- You are comfortable working close to users and product teams, while translating messy qualitative signals into measurement that other modelling teams can act on
- You are self-directed, practical, and motivated by open-ended problems where the right answer requires both technical depth and product understanding
- You care about making AI systems genuinely useful in real enterprise settings, not just better on abstract benchmarks
- If some of the above does not line up perfectly with your experience, we still encourage you to apply
What the job involves
- This role is about being the voice of North inside modelling. You will build the evaluation systems, feedback loops, and applied modelling workflows that make sure model progress translates into better product outcomes for North users
- You will work closely with North product teams, customer-facing teams, and modelling teams to define what “good” means across the product surface, turn real usage and product direction into high-quality evals, and use those evals to guide model selection, patches, and regular model updates
- This is neither a pure research role nor a conventional product engineering role
- Own the eval strategy for North: define what we need to measure across agent workflows, tool use, enterprise knowledge work such as deep research, document creation or editing, and other human-AI interactions
- Build high-quality evals from the realities of the product: user feedback, production failures, privacy-preserving usage logs, internal dogfooding, customer needs, and forward-looking product goals
- Create systems that continuously turn what North is learning from users, customers, and feature teams into evals, so measurement keeps pace with the product rather than becoming a static benchmark
- Be the voice of North inside modelling: extract clear insight from eval results, customer-derived data and product context, then turn model failures, capability gaps, and North-specific needs into actionable recommendations for the central modelling teams
Our take
Many businesses are now faced with the challenge of adopting advanced AI safely and securely. While AI tools like ChatGPT are making headlines, companies (especially those in regulated industries such as banking, telecoms, or government services) worry about privacy, compliance, and control over their sensitive data. Cohere addresses these concerns by offering AI solutions that can be trained on a company's internal data and, importantly, run on their own infrastructure rather than relying on external cloud providers. And in a world where data breaches and regulatory scrutiny are constant threats, this focus on trust and security is key.
In a competitive landscape dominated by giants like OpenAI, Google, and Elon Musk's xAI, Cohere is setting itself apart by targeting businesses exclusively. Its approach has earned it contracts with some big names, like Royal Bank of Canada, Fujitsu, LG, Oracle, and Dell. By focusing on reliability and enterprise adoption rather than viral consumer appeal, Cohere has carved out a strong niche for itself.
This isn't going unnoticed either, as the company recently raised $500M, boosting its valuation to $6.8B, and brought on board top talent from Meta and Uber to strengthen its leadership team. Alongside this, it's doubled its annual recurring revenue to $100M in 2025 and is aiming to hit $200M by year-end. With its North platform for AI agents and a lean cost structure compared with larger rivals, Cohere is very much ready for more growth.
Steph
Company Specialist at Welcome to the Jungle
Insights
192% employee growth in 12 months
Company
Funding (last 2 of 8 rounds)
Apr 2026
$600m
SERIES E
Sep 2025
$100m
LATE VC
Total funding: $2.1bn
Company benefits
- Six weeks’ paid vacation
- Equity / stock options
- RRSP, 401(k), and Pension Scheme contributions
- Coverage for 100% of your insurance premiums across health, dental, vision, and travel
- Additional coverage for accessing mental health providers/services
- Six months of fully paid parental leave, including adoption and surrogacy
- Financial support for egg freezing and IVF in Canada and the UK
- A monthly fitness and wellness allowance
- Globally dispersed company that supports a remote work culture
- A $2,000 annual education benefit for professional development
- A weekly stipend for meals when working remotely and catered lunch when working from one of our global offices
- A monthly arts and culture allowance
- A monthly quality time allowance
Company HQ
Grange Park, Toronto, ON
Leadership
Aidan Gomez
(Co-Founder & CEO)Aidan received a PhD in Computer Science from the University of Oxford in 2024 and has served as Cohere's CEO since co-founding the company in 2019.
Share this job
View 80 more jobs at Cohere