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DevOps Engineer · Philippines

ML Infrastructure Engineer

clera·San Mateo

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ABOUT THE ROLE

This is a hands-on ML Infrastructure Engineer role at an early-stage enterprise AI company building a context and data governance layer that makes AI agents reliable in production. You will own the inference and model-serving infrastructure end to end, ensuring agents run fast and reliably at increasing concurrency. The work is squarely production-focused with real-world impact across regulated industries like insurance, banking, healthcare, and asset management.

WHAT YOU'LL DO

  • Design, build, and scale inference and model-serving infrastructure from the ground up through production deployment.
  • Optimize systems for latency, throughput, and reliability under high concurrency.
  • Collaborate closely with ML and infrastructure teams to ensure seamless integration and surface performance bottlenecks.
  • Drive solutions to infrastructure challenges across a fast-moving, cross-functional team.

WHAT WE'RE LOOKING FOR

  • 5 or more years building and operating machine learning inference systems, model-serving platforms, or ML infrastructure in production environments.
  • Hands-on experience designing and scaling inference-serving systems using tools such as TensorFlow Serving, TorchServe, Triton, KServe, or equivalent custom solutions.
  • Strong distributed systems fundamentals, including containerization and orchestration with Docker and Kubernetes.
  • Proficiency with monitoring and observability tooling for production systems, such as Prometheus, Grafana, or distributed tracing frameworks.
  • Experience deploying and managing ML workloads on cloud platforms (AWS, GCP, or Azure).
  • Proficiency in at least one systems or backend language: Python, Go, Rust, C++, or Java.
  • Comfort collaborating across both ML and infrastructure disciplines in a fast-paced environment.
  • Nice to have: experience with knowledge graphs, semantic search, or graph databases; real-time or low-latency inference systems; agentic or multi-step AI pipelines; enterprise data integration or pipeline infrastructure.

LOCATION

On-site in San Mateo, California, United States. Visa sponsorship is not available for this role.

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