Machine Learning Operations Engineer
Job Description:
Machine Learning Operations (MLOps) Engineer
We’re a naan traditional company…
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.
What FGF Offers:
- FGF believes in Home Grown Talent, accelerated career growth with leadership training. Unleashing Your Potential
- Competitive Compensation, Health Benefits, & a generous flexible medical / Health spending account
- RRSP matching program
- Tuition reimbursement
- Discount program that covers almost everything under the sun - Restaurants, gyms, shopping etc.
Primary Responsibilities
MLOps- Deploy machine learning models on hardware platforms with a focus on edge AI and IoT systems.
- Leverage containerization (e.g., Docker) for scalable, repeatable deployments.
- Automate workflows to streamline machine learning pipelines and maximize reproducibility.
- Build and configure development boards such as NVIDIA boards or similar platforms.
- Integrate cameras and peripherals for AI and computer vision applications.
- Diagnose and resolve hardware issues, ensuring peak system performance.
- Establish seamless network connectivity for IoT devices and integrated systems.
- Maintain hardware inventory and detailed documentation of all configurations and workflows.
- Support data collection initiatives by designing and integrating sensor and camera systems.
- Partner with teams to create customized hardware solutions tailored to project needs.
- Maintain on-premises and edge AI setups to support real-time applications.
Required Experience
Education and Experience- Education in computer science and electrical engineering with minimum 5 years of experience in related roles or similar technical field of study.
- Deep familiarity with platforms like NVIDIA Boards, Raspberry Pi, or comparable devices.
- Knowledge of Linux environment, machine learning workflows and MLOps best practices.
- Proficiency in setting up hardware systems, including advanced troubleshooting.
- Experience with containerization (Docker) and cloud services integration.
- Proficiency in Python; familiarity with ML frameworks like PyTorch, Tensorflow is a plus
- Experience with hardware acceleration tools such as NVIDIA TensorRT is advantageous.
- 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.
In compliance with Ontario’s Bill 190, we confirm that this posting represents a current, existing vacancy within our organization.
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.
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