Senior ML Operations (MLOps) Engineer
Core
Design and operate robust ML infrastructure to deploy and scale machine learning models for health monitoring in smart sleep devices.
Role type
Senior IC MLOps Engineer
Builds
Scalable data, model, and deployment pipelines for ML inference on device fleets
Domain
Health tech / IoT / Wearables
Deliverable
production ML models
Required skills
Python, PyTorch, TensorFlow, ML workflow orchestration, CI/CD for model deployment, cloud-native architecture, distributed systems, large-scale data processing
Preferred skills
Real-time ML workflows, streaming systems (Kinesis, Kafka, Flink), cost optimization, secure ML operations
Technologies
AWS (Lambda, ECS, DynamoDB, CloudWatch), PyTorch, TensorFlow, Kinesis, Kafka, Flink
Responsibilities
Design and implement ML infrastructure pipelines, optimize compute and storage resources, develop tooling for data processing and deployment, collaborate with R&D and firmware teams for reliable inference
Seniority
Senior, hands-on IC
