Machine Learning Operations Engineer

fgf brands

$90K — $110K *
Information Technology
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • 5-7 years of experience in MLOps and hardware support
  • Deep familiarity with Linux environments
  • Proficiency in Python and familiarity with ML frameworks
  • Experience with containerization tools like Docker
  • Solid knowledge of NVIDIA Boards and Raspberry Pi
  • Strong troubleshooting capabilities in production settings
  • Excellent communication and teamwork skills

Responsibilities

  • Deploy machine learning models on edge AI and IoT hardware
  • Set up servers for production ML workloads
  • Leverage Docker for scalable deployments
  • Maintain servers and vision models for uptime and reliability
  • Troubleshoot production model issues with timely resolutions
  • Automate workflows to enhance machine learning pipelines

Benefits

  • Opportunities for career growth in a dynamic environment
  • Encouragement of creativity and out-of-the-box thinking
  • Engagement in challenging and rewarding work
  • Supportive team culture fostering collaboration
Full Job Description
Job Description

MLOps & Production Support Specialist

Summary

We are looking for a versatile and hands-on individual who thrives on working with hardware, machine learning operations (MLOps), and supporting a dynamic data science team. The ideal candidate will have a broad technical skill set and the ability to tackle various challenges, including hardware setup, system optimization, and machine learning workflows.

Primary Responsibilities

  • Deploy machine learning models on hardware platforms with a focus on edge AI and IoT systems.
  • Set up servers and deploy models to support production ML workloads.
  • Leverage containerization (e.g., Docker) for scalable, repeatable deployments.
  • Support and maintain servers and vision models running in production, ensuring uptime, performance, and reliability.
  • Troubleshoot and resolve support tickets related to production model issues, providing timely fixes and root-cause analysis.
  • Automate workflows to streamline machine learning pipelines and maximize reproducibility.

Required Experience

Technical Expertise
  • Deep familiarity with Linux environment, machine learning workflows and MLOps best practices.
  • Knowledge of platforms like NVIDIA Boards, Raspberry Pi, or comparable devices.
  • Proficiency in setting up hardware systems, including advanced troubleshooting.
  • Experience with containerization (Docker) and cloud services integration.
  • Experience with server setup, configuration, and ongoing maintenance in production environments.
  • Experience deploying and supporting vision models in production, including monitoring and troubleshooting live inference systems.
  • Comfortable managing and resolving support tickets tied to production model issues.

Programming Skills
  • Proficiency in Python; familiarity with ML frameworks like PyTorch, Tensorflow is a plus.
  • Experience with hardware acceleration tools such as NVIDIA TensorRT is advantageous.

Problem Solving & Collaboration
  • A relentless drive to find elegant, scalable solutions to complex problems.
  • Strong communication skills and a commitment to teamwork.

What is the recipe for a great career at FGF?
Working at FGF Brands, there is never a dull moment! As a successful company that is continually growing there is always challenging yet rewarding work to be a part of. We have an entrepreneurial spirit which encourages all our team members to use their own creativity and out of the box thinking to come up with solutions and new ideas.

Disclaimer: The above describes the general responsibilities, required knowledge and skills. Please keep in mind that other duties may be added or this description may be amended at any time.

In compliance with Ontario's Bill 190, we confirm that this posting represents a current, existing vacancy within our organization

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