Senior/Staff MLE
Cohere
full-time
Posted on:
Location Type: Remote
Location: California • United States
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Job Level
Tech Stack
About the role
- Work directly with enterprise customers on problems that push LLMs to their limits.
- Train and customize frontier models — not just use APIs.
- Influence the capabilities of Cohere’s foundation models.
- Operate with an early-startup level of ownership inside a frontier-model company.
- Wear multiple hats, set a high technical bar, and define what Applied ML at Cohere becomes.
- Lead the design and delivery of custom LLM solutions for enterprise customers.
- Translate ambiguous business problems into well-framed ML problems with clear success criteria and evaluation methodologies.
- Build custom models using Cohere’s foundation model stack, CPT recipes, post-training pipelines (including RLVR), and data assets.
- Develop SOTA modeling techniques that directly enhance model performance for customer use-cases.
- Contribute improvements back to the foundation-model stack — including new capabilities, tuning strategies, and evaluation frameworks.
- Work closely with enterprise customers to identify high-value opportunities where LLMs can unlock transformative impact.
- Provide technical leadership across discovery, scoping, modeling, deployment, agent workflows, and post-deployment iteration.
- Establish evaluation frameworks and success metrics for custom modeling engagements.
- Mentor engineers across distributed teams.
- Drive clarity in ambiguous situations, build alignment, and raise engineering and modeling quality across the organization.
Requirements
- Strong ML fundamentals and the ability to frame complex, ambiguous problems as ML solutions.
- Fluency with Python and core ML/LLM frameworks.
- Experience working with large-scale datasets and distributed training or inference pipelines.
- Understanding of LLM architectures, tuning techniques (CPT, post-training), and evaluation methodologies.
- Demonstrated ability to meaningfully shape LLM performance.
- Experience engaging directly with customers or stakeholders to design and deliver ML-powered solutions.
- A track record of technical leadership at a team level.
- A broad view of the ML research landscape and a desire to push the state of the art.
- Bias toward action, high ownership, and comfort with ambiguity.
- Humility and strong collaboration instincts.
- A deep conviction that AI should meaningfully empower people and organizations.
Benefits
- An open and inclusive culture and work environment
- Work closely with a team on the cutting edge of AI research
- Weekly lunch stipend, in-office lunches & snacks
- Full health and dental benefits, including a separate budget to take care of your mental health
- 100% Parental Leave top-up for up to 6 months
- Personal enrichment benefits towards arts and culture, fitness and well-being, quality time, and workspace improvement
- Remote-flexible, offices in Toronto, New York, San Francisco, London and Paris, as well as a co-working stipend
- 6 weeks of vacation (30 working days!)
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
machine learninglarge language modelsPythonCPTpost-training pipelinesSOTA modeling techniquesevaluation methodologiesdistributed traininginference pipelinescustom model development
Soft Skills
technical leadershipproblem framingcollaborationmentoringownershipambiguity managementinfluencecommunicationalignment buildingcustomer engagement