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Senior MLOps Engineer - Edge

1 month, 3 weeks ago
Spain, United Kingdom
Full-time
Senior
Machine Learning Engineer
DevOps and Infrastructure
CI/CD Docker Linux MLOps Neural Networks Python
Apply Now
Hudl

Hudl

Hudl provides a platform and software that enables sports teams, coaches, and athletes to capture, analyze, and learn from video and data, enhancing their performance across various sports.

Diversified Consumer Services
1K-5K
Founded 2006
$109M raised
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Description

  • Design, develop, and maintain edge infrastructure for deploying models to fleets of devices.
  • Build and own the model compilation platform that turns trained models into hardware-specific inference engines.
  • Manage TensorRT compilation, precision trade-offs, calibration, and engine validation.
  • Collaborate with Data Scientists, Embedded Engineers, and Product Managers to integrate new capabilities.
  • Implement automation to test candidate models on production devices and monitor model drift, thermal impact, and inference latency.
  • Build resilient update mechanisms for low-bandwidth environments and devices with limited storage.
  • Ensure devices recover gracefully from network failures and other edge deployment issues.
  • Establish best practices for Python tooling, Infrastructure-as-Code, and CI/CD.
  • Mentor and guide the team toward more robust and automated delivery processes.

Requirements

  • Production MLOps experience building and operating model deployment pipelines.
  • Deep experience with CI/CD, Docker, and Linux systems.
  • Hands-on experience compiling and optimizing models for embedded hardware, ideally with TensorRT.
  • Understanding of precision, quantization, and engine validation at scale.
  • Ability to communicate effectively with researchers and embedded engineers.
  • Systems-thinking approach to designing failure-resistant architectures for large heterogeneous device fleets.
  • Ability to manage risk through canary releases and safe rollbacks.
  • Bias toward action and willingness to take initiative to solve problems.
  • Experience with the NVIDIA edge ecosystem, including Jetson Orin, DeepStream SDK, and TensorRT, is a plus.
  • Familiarity with video pipelines, GStreamer, or ffmpeg is a plus.
  • Experience with fleet management tools such as AWS IoT Greengrass, Balena, or custom OTA solutions is a plus.
  • Interest in sports technology, video analytics, or performance metrics is a plus.
  • Must live near the London or Barcelona offices, or be based remotely in the UK or Spain.

Benefits

  • Flexible vacation time, company-wide holidays, and meeting-free timeout days.
  • Remote work options.
  • Strong autonomy and ownership over your work.
  • Professional development resources and growth opportunities.
  • Tech stack and hardware provided for office or remote work.
  • Medical and retirement benefits depending on location.
  • Employee Assistance Program for mental health support.
  • Employee resource groups and inclusion communities.

Interested in this position?

Apply directly on the company website

Apply Now

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