Senior ML Operations (MLOps) Engineer
Remote regions
USBenefits
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.