About the job
Senior AI/ML Engineer
Location: Ottawa, ON | Hybrid
Department: Engineering
Reports To: Eugenia Kondratova, Senior Technical Manager, AI
Type: Full-Time | Permanent
Vacancy Status: This is an active role and we are currently hiring for this position.
About Solink
At Solink, we are dedicated to protecting what matters most. Our mission is to empower businesses with real-time operational insights by transforming video security. Our innovative cloud-based platform seamlessly integrates with existing camera systems, turning them into intelligent sensors that detect and interpret critical moments. This enables teams to make informed, data-driven decisions, thereby enhancing security and operational efficiency.
With over 30,000 locations in more than 32 countries, including well-known brands such as McDonald's and JYSK, Solink provides clarity when it is most needed. Our solutions assist businesses in minimizing shrinkage, optimizing their operations, and proactively addressing emerging threats.
We are experiencing rapid growth and have received accolades from Deloitte’s Fast 50™ and Fast 500™ and recognition as one of Ottawa’s Best Places to Work. We are just getting started!
The Role
As a Senior AI/ML Engineer at Solink, you will be responsible for designing, building, and deploying comprehensive machine learning solutions that drive our next generation of video analytics and operational intelligence. Your work will span research, model development, software engineering, and production integration, where you will own features that deliver significant value to our customers in both cloud and edge environments.
This position is perfect for individuals who excel in fast-paced environments, relish tackling complex technical challenges, and are driven by the opportunity to deliver reliable, scalable ML-powered features used in high-demand, real-world applications.
What You’ll Do
Design, develop, train, and deploy ML models—including computer vision, LLMs/VLMs, and multimodal models—across cloud and edge/embedded environments.
Own ML-driven features end-to-end: from proof of concept and experimentation to integration, deployment, instrumentation, and continuous improvement.
Evaluate and integrate third-party AI/LLM/VLM services, balancing cost, performance, and scalability.

