ML Developer Experience Engineer
About the TeamAdaptive ML is a frontier AI startup building a Reinforcement Learning Operations (RLOps) platform that enables enterprises to specialise and deploy LLMs into production with measurable impact. We provide the core infrastructure to tune, evaluate, and serve specialised models at scale — pioneering task-specific LLM development and running production-ready workflows that serve millions of requests while optimising 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, and Deloitte, across travel and financial services — with much more to be announced soon.
About the RoleWe’re looking for an ML Developer Experience Engineer to empower ML engineers and developer teams to leverage reinforcement learning without needing deep RL expertise. You’ll build developer-centric tooling, abstractions, and workflows that make training, evaluating, and deploying RL models intuitive, robust, and scalable — fuelling our customers’ ability to adopt, expand, and own RL use cases.
This role is core to our land-and-expand strategy: your work will enable customers to scale independently, reducing friction and unlocking self-service adoption across organisations. You’ll collaborate closely with Technical Success, Product, and Engineering to identify patterns, extract reusable solutions, and shape the boundary between tooling and product.
This role is based in Paris, New York, or Toronto.
Your ResponsibilitiesDesign and build intuitive SDKs, libraries, APIs, and tooling that make RL workflows accessible and productive for developers and ML engineers.
Balance simplicity and flexibility — support common patterns while enabling advanced configurations and extensibility.
Partner with internal teams to refine primitives into documented, reusable modules that accelerate customer success.
Work across the technical and customer success teams to identify recurring customer patterns and workflow bottlenecks.
Translate feedback into tooling improvements, error messaging, onboarding flows, and reference examples.
Own comprehensive documentation, examples, and tutorials that make complex concepts clear and approachable.
Act as the translator between customer needs and product evolution — help shape internal libraries into long-term platform capabilities.
Ensure high quality through tests, edge-case handling, and reliability as a core tenet of the developer experience.
Collaborate with Product to influence roadmap decisions with real usage and pain-point insights.
We encourage candidates to apply even if their experience doesn’t match every point below.
Experience building developer-facing libraries, tooling, SDKs, APIs, or frameworks used in production by other developers or teams.
Comfort with Python (mandatory) and/or other languages common in the ML ecosystem.
Track record of elevating developer productivity and satisfaction through documentation, design, and feedback loops.
Understanding of ML workflows, training loops, evaluation, and deployment patterns — RL familiarity is a plus, not a prerequisite.
Empathy for developers as users — you understand that clarity and usability drive adoption.
Strong collaborative skills and ability to influence across technical and customer-facing teams.
Contributions to open-source tooling or developer libraries.
Experience with distributed training, PyTorch/JAX, or developer platform tools (e.g., language server integrations, CLI frameworks, documentation systems).
Experience shaping developer experience strategy in a product organisation.
Strong interest in Rust.
Competitive compensation package benchmarked to local market.
Private health insurance (or top-up to national coverage, depending on location).
Pension contribution or equivalent retirement benefit.
Unlimited PTO — we strongly encourage at least 5 weeks each year (in addition to local statutory leave).
Mental health, wellness, and personal development stipends.
Visa sponsorship available if you wish to relocate to Paris.
Skills Required
- Experience building developer-facing libraries, tooling, SDKs, APIs, or frameworks
- Comfort with Python
- Understanding of ML workflows, training loops, evaluation, and deployment patterns
What We Do
Continuously evaluate and adapt models with synthetic data and production feedback to surpass frontier performance—from your cloud or ours
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