Senior ML Operations (MLOps) Engineer

Eight Sleep
United States
Workplace: RemoteFull timeFunction: Solutions Engineering & Sales EngineeringExperience: 5+ yearsSkills: ["Remote communication","Cross-functional collaboration","Iterative problem-solving","Adaptive approach"]

Build and operate ML infrastructure that brings pod model pipelines from design through production. You’ll own scalable data, model, and deployment workflows, optimize compute/storage/deployment costs, and ensure reliable ML inference across devices worldwide. Working closely with R&D, firmware, data, and backend teams, you’ll develop tooling, microservices, and frameworks to streamline experimentation and deployment while instrumenting telemetry, monitoring, and feedback loops for continuous improvement.

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FursaFursa
Eight Sleep
Eight Sleep
11 months ago

Senior ML Operations (MLOps) Engineer

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Source: Company careers pageValidated by: Fursa AI
Last checked: 21 hours agoStatus: Live

Job Summary

Build and operate ML infrastructure that brings pod model pipelines from design through production. You’ll own scalable data, model, and deployment workflows, optimize compute/storage/deployment costs, and ensure reliable ML inference across devices worldwide. Working closely with R&D, firmware, data, and backend teams, you’ll develop tooling, microservices, and frameworks to streamline experimentation and deployment while instrumenting telemetry, monitoring, and feedback loops for continuous improvement.
Location: United States
Workplace: Remote
Employment Type: Full time
Job Function: Solutions Engineering & Sales Engineering
Seniority: Mid level

Key Responsibilities

  • •Design and implement cutting-edge ML technologies and integrate them into products and processes.
  • •Own the design and operation of robust ML infrastructure, including scalable data, model, and deployment pipelines for production delivery.
  • •Collaborate with R&D, firmware, data, and backend teams to ensure ML inference reliability and scalability across pods.
  • •Optimize compute, storage, and deployment resources to improve performance, latency, and cost-effectiveness.
  • •Develop tooling, microservices, and frameworks to streamline data processing, experimentation, and deployment.

Pay and Benefits

Equity and Bonus:Equity
Perks:Health InsuranceVisionDentalLife InsurancePaid LeaveCommuter BenefitsPaid Parental

Key Requirements

  • •5+ years of software engineering experience focused on ML infrastructure, distributed systems, or large-scale data processing in Python (e.g., PyTorch or TensorFlow).
  • •Hands-on ML workflow orchestration experience with CI/CD pipelines for model deployment.
  • •Experience shipping ML models to production at scale, including telemetry, monitoring, and feedback loops across large device fleets or user populations.
  • •Strong AWS experience for serving and monitoring ML systems (e.g., Lambda, ECS, DynamoDB, CloudWatch).
  • •Experience with real-time ML workflows and streaming systems (e.g., Kinesis, Kafka, Flink).
Experience:5+ yearsMachine learningDistributed systemsLarge-scale data processingReal-time streamingHealth/wellnessIoTDevice fleets
Skills:Remote communicationCross-functional collaborationIterative problem-solvingAdaptive approach
Tech Stack:PythonPyTorchTensorFlowAWSLambdaECSDynamoDBCloudWatchKinesisKafkaFlink

Company Brief

Eight Sleep
Eight Sleep makes AI-powered sleep hardware and software (the Pod) that monitors biometrics and adjusts temperature, elevation, and sound to improve sleep and recovery for consumers and clinical applications. Recent expansion targets medical use cases and global retail. ([crunchbase.com](https://www.crunchbase.com/organization/eight-sleep?utm_source=openai))
Industry: Wellness & Preventive Health
Company Size: Medium (51 to 250 employees)
Growth: Scaleup
Valuation: USD 250M to 500M
Funding: Series D
Headquarters: New York, United States
Founded: 2014
Glassdoor
Glassdoor: 3.8
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