Senior MLOps Engineer - Edge

Hudl
Barcelona, London
Full timeFunction: Solutions Engineering & Sales EngineeringSkills: ["Collaboration","Systems thinking","Automation mindset","Problem-solving","Mentoring"]

Build and scale edge machine learning infrastructure for smart cameras, owning deployment pipelines that move neural networks from training clusters to tens of thousands of devices. Create and maintain a model compilation platform that produces hardware-specific inference engines, including TensorRT compilation and precision/validation work. Collaborate with data science, embedded engineering, and product to drive automated testing, telemetry for drift/latency/thermal impact, and resilient updates for low-bandwidth environments.

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Hudl
Hudl
1 day ago

Senior MLOps Engineer - Edge

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Last checked: 10 hours agoStatus: Live

Job Summary

Build and scale edge machine learning infrastructure for smart cameras, owning deployment pipelines that move neural networks from training clusters to tens of thousands of devices. Create and maintain a model compilation platform that produces hardware-specific inference engines, including TensorRT compilation and precision/validation work. Collaborate with data science, embedded engineering, and product to drive automated testing, telemetry for drift/latency/thermal impact, and resilient updates for low-bandwidth environments.
Location: Barcelona, London
Employment Type: Full time
Job Function: Solutions Engineering & Sales Engineering
Seniority: Mid level

Key Responsibilities

  • •Design, develop, and maintain edge deployment infrastructure to deliver models to fleets of devices at global scale.
  • •Build and maintain the model compilation pipeline that converts trained models into optimized, hardware-specific inference engines and validates performance reliably.
  • •Implement automation and reliability features, including silent testing on production devices and telemetry pipelines for drift, thermal impact, and inference latency.
  • •Collaborate with Data Scientists, Embedded Engineers, and Product Managers to integrate complex capabilities and ensure smooth end-to-end delivery.
  • •Lead and mentor by establishing best practices for Python tooling, Infrastructure-as-Code, and CI/CD while guiding the team toward robust automation.

Pay and Benefits

Perks:MedicalRetirementRemote WorkEmployee Assistance

Key Requirements

  • •Production MLOps experience building and operating pipelines to deploy models to production using CI/CD, containerization (Docker), and Linux systems.
  • •Hands-on edge inference and compilation experience for embedded hardware, ideally including TensorRT, plus understanding precision trade-offs (FP16/INT8), quantization, and engine validation.
  • •Strong collaboration skills translating constraints between Data Scientists, Embedded Engineers, and stakeholders to ship models to hardware.
  • •Systems thinking for reliable architectures at scale, including canary releases, safe rollbacks, and graceful failure handling.
  • •Proactive problem-solving mindset with a bias toward action to fill gaps and improve reliability and automation.
Experience:MLOpsMachine learningEdge AIEmbedded hardware
Skills:CollaborationSystems thinkingAutomation mindsetProblem-solvingMentoring
Languages:English
Tech Stack:PythonInfrastructure-as-CodeCI/CDDockerLinuxTensorRTFP16INT8CalibrationEngine validationJetson OrinDeepStream SDKGStreamerFfmpegAWS IoT GreengrassBalena

Company Brief

Hudl
Provides video analysis and performance tools for sports teams and athletes, offering software to capture, review, and share game footage and analytics across youth, amateur, and professional sports organizations.
Industry: Enterprise Software
Company Size: Enterprise (1,001+ employees)
Growth: Established Company
Headquarters: Lincoln, United States
Founded: 2006
WebsiteLinkedIn