Member of Technical Staff, MLE
Remote • San Francisco • FullTime
Posted 6mo ago
Remote Work Policy
Fully remote
Employment Type
FullTime
Categories
Applied AI Engineer
About the job
Cohere is seeking a Member of Technical Staff, Applied ML to work directly with enterprise customers on challenging problems that push the limits of Large Language Models (LLMs). In this role, you will gain a deep understanding of customer domains, design custom LLM solutions, and deliver production-ready models to solve high-value business problems. You will not just use APIs, but will train and customize frontier models using Cohere's full stack, including CPT, post-training, retrieval and agent integrations, model evaluations, and state-of-the-art modeling techniques. Your work will directly influence the capabilities of Cohere's foundation models, shaping their next generation. This role offers a unique opportunity to combine the breadth of an early-stage CTO with the infrastructure and scale of a deep-learning lab, requiring you to wear multiple hats, set a high technical bar, and define the future of Applied ML at Cohere.
Responsibilities
- Contribute to 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 state-of-the-art 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 as part of Cohere’s customer-facing MLE team to identify high-value opportunities where LLMs can unlock transformative impact for enterprise customers.
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.
- 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
- 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.
- A co-working benefit for those not near an office.
- $500 home office stipend to set up your workspace properly.