Forward Deployed AI Engineer

Adaptive ML is a frontier AI startup building a Reinforcement Learning Operations (RLOps) platform that enables enterprises to specialize and deploy LLMs into production with measurable impact.

We provide the core infrastructure to tune, evaluate, and serve specialized models at scale — pioneering task-specific LLM development and running production-ready workflows that serve millions of requests while optimizing for both cost and performance across distributed systems.

Our tightly-knit team was previously involved in the creation of state-of-the-art open-access large language models. We raised a $20M seed led by Index Ventures and ICONIQ in early 2024, and we're already live in production with customers including Manulife, AT&T, Deloitte, across travel and financial services — with much more to be announced soon.

At Adaptive ML, our Success team is part of our Technical Staff. Our Technical Staff develops the foundational technology that powers Adaptive ML, while the Success Team ensures our enterprise customers effectively leverage these technologies—particularly through our Adaptive Engine product—to unlock maximum value. 

As a Forward Deployed AI Engineer at Adaptive ML, you will help our customers build scalable production applications with Adaptive Engine. Our customers range from innovative scale-ups to global enterprises, and your role will be to guide them in maximizing business value while shortening time to production. We place tremendous importance on bridging the gap from proof-of-concept to production, as too many generative AI projects fail to demonstrate tangible ROI.

By leveraging state-of-the-art reinforcement learning technology, you will support the specialization of large language models for production deployment. You will build synthetic data pipelines to bootstrap models into production and identify signals that can be used in production to enable continuous model improvement using production feedback. We are looking for self-driven, business-minded, and ambitious individuals interested in supporting real-world deployments of a highly technical product. As this is an early role, you will have the opportunity to shape our research efforts and product as we grow.

This is an in-person role based at our Toronto or New York office.

• Embed directly with our customers, helping them maximize the value of their Adaptive Engine deployment;

• Experiment with pipelines to personalize models at scale, leveraging synthetic data and production feedback;

• Ensure customer success, owning problems end-to-end from ideation to deployment, validation, and production;

• Work closely with our research staff, productionizing the latest frontier research initiatives;

• Contribute to our product roadmap, identifying promising trends and customer needs;

• Report clearly on your work to a distributed collaborative team, with a bias for asynchronous written communication.

The background below is only suggestive of a few pointers we believe could be relevant. We welcome applications from candidates with diverse backgrounds; do not hesitate to get in touch if you think you could be a great fit, even if the below doesn't fully describe you.

• ‍A M.Sc./Ph.D. in computer science, or demonstrated experience in software engineering, preferably with a focus on machine learning;

• 4-8+ years of technical consulting (or equivalent) experience;‍

• Strong programming skills, with Python experience required, from quick prototyping to production deployments;

• Enthusiasm for collaborating with diverse technical teams, with a humble attitude and empathy;‍

• Passionate about the future of generative AI, and eager to build foundational technology to help machines deliver more singular experiences.

• Comprehensive medical (health, dental, and vision) insurance;

• 401(k) plan with 4% matching (or equivalent);

• Unlimited PTO — we strongly encourage at least 5 weeks each year;

• Mental health, wellness, and personal development stipends;

• Visa sponsorship if you wish to relocate to New York or Paris.