Responsibilities
- deployment).
- Drive adoption of ML Platform tools and services through hands-on integration support, examples, and pragmatic guidance.
- Guide the evolution of ML Platform tooling based on real user needs (identify friction, propose improvements, validate with users, help ship changes).
- Establish and promote standards for ML development: reproducibility, quality, auditability, and maintainability (testing, versioning, documentation).
- Build self-service tooling (libraries, templates, reference implementations, automation) to reduce dependency on the platform team.
- Improve production readiness of ML systems: CI/CD, environment consistency, monitoring/alerting, incident readiness, and safe rollout practices.
- Mentor junior team members as the team expands; teach by building (docs, examples, office hours, paired debugging).
- Advocate for industry best practices in ML-related software engineering across the company.
Preferred qualifications
Technical:
Experience as a Data Scientist (useful for empathy with research workflows and evaluation practices).
Experience with inference servers (e.g., Triton) or building production model-serving services (HTTP/gRPC, scaling, latency/throughput tradeoffs).
Platform design / software architecture experience (APIs, multi-tenant systems, shared libraries, backwards compatibility).
Experience with C++/Python interoperability (e.g., bindings) and performance profiling across language boundaries.
“Design thinking” applied to platform work: identifying user journeys, reducing cognitive load, making the right thing the easy thing.
If you don’t meet every requirement but believe you’d be a great fit, feel free to reach out to us.
EQUAL OPPORTUNITIES STATEMENT
We are continuously striving to be an equal opportunity employer and we prohibit any discrimination based on sex, disability, origin, sexual orientation, gender identity, age, race, or religion. We believe that our diversity, breadth of experience, and multiple points of view are among the leading factors in our success.
CFM is a signatory of the Women Empowerment Principles.
About the company
- building and improving Python-first tooling and patterns,
- ensuring solutions are production-ready (MLOps, reliability, monitoring),
- and occasionally diving into C++ parts of the stack to debug issues, investigate performance bottlenecks, or contribute fixes in collaboration with owners.