ML Engineer
Responsibilities
- check_circle deployment).
- check_circle Drive adoption of ML Platform tools and services through hands-on integration support, examples, and pragmatic guidance.
- check_circle Guide the evolution of ML Platform tooling based on real user needs (identify friction, propose improvements, validate with users, help ship changes).
- check_circle Establish and promote standards for ML development: reproducibility, quality, auditability, and maintainability (testing, versioning, documentation).
- check_circle Build self-service tooling (libraries, templates, reference implementations, automation) to reduce dependency on the platform team.
- check_circle Improve production readiness of ML systems: CI/CD, environment consistency, monitoring/alerting, incident readiness, and safe rollout practices.
- check_circle Mentor junior team members as the team expands; teach by building (docs, examples, office hours, paired debugging).
- check_circle 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
- check_circle building and improving Python-first tooling and patterns,
- check_circle ensuring solutions are production-ready (MLOps, reliability, monitoring),
- check_circle and occasionally diving into C++ parts of the stack to debug issues, investigate performance bottlenecks, or contribute fixes in collaboration with owners.