Senior ML Operations Engineer

Role overview

As a Senior ML Operations Engineer, you will help bring Eight Sleep’s Pod ML models to life. You will design and operate robust ML infrastructure, and collaborate with cross-functional teams to ensure production-ready ML inference.

Key missions

• Conception et mise en œuvre de solutions ML to improve members’ sleep.
• Design and operate a robust ML infrastructure, including data, model, and deployment pipelines.
• Partner with R&D, firmware, data, and backend teams to ensure reliable ML inference.

Responsibilities

• Build and run production ML workflows and infrastructure.
• Ensure end-to-end operation from data/model pipelines to deployment.
• Implement telemetry, monitoring, and feedback loops for models in production.
• Optimize ML infrastructure for efficiency, latency, and cloud cost.

Requirements

• 5+ years of software engineering, focused on ML infrastructure, distributed systems, or large-scale data processing in Python (e.g., PyTorch / TensorFlow or similar).
• Experience shipping ML models to production at scale, including telemetry, monitoring, and feedback loops across device fleets or users.
• Hands-on ML Ops experience with workflow orchestration and CI/CD pipelines for model deployment.
• Strong cloud-native skills with AWS (e.g., Lambda, ECS, DynamoDB, CloudWatch) or equivalent.
• Real-time ML workflows and streaming systems (e.g., Kinesis, Kafka, Flink).
• Secure ML operations and privacy/compliance considerations, especially for health/IoT data.

Nice-to-haves

• Familiarity with health, wellness, or IoT domains, especially wearables or medical-grade devices.
• Experience operating ML systems across large device/user populations.