Machine Learning Operations Engineer

FGF Brands; Mississauga; On-site; CAD 80,000 - 120,000; Full time

Job summary

An innovative firm is seeking a Machine Learning Operations Engineer to join their dynamic team. This role involves deploying machine learning models on cutting-edge hardware platforms, optimizing systems for peak performance, and collaborating closely with data scientists. The ideal candidate will have a strong technical background in computer science and electrical engineering, with hands-on experience in MLOps, hardware integration, and problem-solving. Join a forward-thinking organization that values home-grown talent and offers numerous benefits, including competitive compensation and career growth opportunities. If you're passionate about technology and eager to make an impact, this is the perfect opportunity for you.

Benefits

Health Benefits

Flexible Medical Spending Account

RRSP Matching Program

Tuition Reimbursement

Discount Program

Qualifications

• 5+ years of experience in MLOps and hardware engineering.
• Deep familiarity with NVIDIA Boards and containerization tools.

Responsibilities

• Deploy machine learning models focusing on edge AI and IoT systems.
• Build and configure development boards and integrate AI peripherals.

Skills

Problem Solving

Collaboration

Communication Skills

Machine Learning Workflows

Hardware Troubleshooting

Education

Computer Science Degree

Electrical Engineering Degree

Tools

Docker

NVIDIA Boards

Raspberry Pi

Linux

TensorFlow

PyTorch

Job description

Job Description

Machine Learning Operations (MLOps) Engineer

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.

Hardware Engineering & Optimization

• 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.

System & Network Configuration

• Establish seamless network connectivity for IoT devices and integrated systems.
• Maintain hardware inventory and detailed documentation of all configurations and workflows.

Collaboration with Data Science Teams

• 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.

Technical Expertise

• 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.

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.

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.