Senior ML Operations (MLOps) Engineer

Jobgether

Remote regions

US

Benefits

Unlimited PTO

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Infrastructure & Scale:

  • Build scalable ML infrastructure including data pipelines, training workflows, and deployment systems.
  • Own end-to-end ML lifecycle operations to ensure reliable delivery of models into production.

Collaboration & Integration:

  • Work closely with R&D, firmware, backend, and data teams for seamless ML inference integration.
  • Build tooling, microservices, and frameworks to improve experimentation and deployment efficiency.

Performance & Observability:

  • Implement monitoring, telemetry, and feedback loops for ML models in production.
  • Optimize compute, storage, and infrastructure costs while maintaining high performance and reliability.

Jobgether

Our partner company develops ML systems for connected hardware products used by customers worldwide. They operate in a fast-paced, product-driven environment with a collaborative and technically ambitious culture focused on real-world ML impact.

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