Machine Learning Engineer

Job summary

Develop, deploy, and maintain production computer vision models across the full machine learning lifecycle. Optimize models for resource-constrained edge devices and establish evaluation methods to connect performance to business outcomes.

Job details

We are looking for a Machine Learning Engineer to join our Toronto team and help us take our products to the next level in terms of visual intelligence. Our Company Invision AI is building a universal AI platform for computer vision applications. Powered by a unique multi-camera stack that generates high-integrity 3D digital twins of dynamic environments, our technology powers disruptive, market-leading solutions in intelligent infrastructure and global Transportation. The Role As a Machine Learning Engineer, you will work across the full machine learning lifecycle, from data collection and labeling strategy through training, evaluation, deployment, monitoring, and ongoing improvement. Your focus will be developing and maintaining computer vision models used in real-world products. While the work may involve researching and implementing new approaches, this is primarily an applied engineering position. We are looking for someone with a track record of building, shipping, and maintaining production ML systems. The position includes working on projects that expand and strengthen our capabilities in object detection, image classification, geospatial tracking, and sensor fusion, with models deployed to resource-constrained edge devices. Working within a collaborative team, you will build accurate, efficient, and principled solutions. As a key contributor to the company's next stage of growth, you will help advance our products, solve challenging customer problems, and shape our ML engineering practices in a fast-moving environment. Location This is a full-time, hybrid position based in Toronto. You will work from our downtown Toronto office three days per week. What You'll Do Recommend, develop, evaluate, and deploy ML models across our product lines Build and improve data-labeling, training, and evaluation pipelines Establish evaluation methods that connect model performance to product and business outcomes Prototype new product capabilities using appropriate technologies Optimize models for latency, memory usage, power consumption, and accuracy on edge devices Diagnose and resolve issues affecting deployed models Monitor production performance and identify model drift, data-quality problems, and retraining needs Write maintainable, well-tested code and clear technical documentation Participate in design reviews, code reviews, and technical planning Share ML knowledge and collaborate with software, product, and other engineering teams Requirements Must Have A track record of developing and deploying production computer vision models Strong Python software development skills Proficiency with frameworks such as PyTorch, TensorFlow and scikit-learn Practical knowledge of CNNs and modern computer vision architectures The ability to adapt open-source models to specific products and use cases Hands-on work optimizing models for resource-constrained or edge environments Knowledge of experiment tracking, dataset versioning, and ML observability Skill in designing evaluation metrics that reflect product and business requirements An understanding of model monitoring and production troubleshooting Working knowledge of embedded systems and their constraints Sound software engineering practices, including automated testing, code review, version control, and continuous integration Strong written and verbal communication skills Bonus Skills Familiarity with Docker or other container technologies C++ development skills GPU programming or performance-optimization knowledge Knowledge of model compression techniques, including quantization, pruning, and knowledge distillation Familiarity with edge inference tools such as ONNX Runtime, TensorRT Familiarity with traditional, non-ML image-processing techniques A background in sensor fusion or geospatial data Benefits A Mission that Matters: The opportunity to work on projects that make the world safer and greener Excellence: A culture of very high technical standards where quality engineering is valued over quick hacks Technical Challenge: A wide variety of technology and tasks, including web development, distributed and edge computing, ML, real-time processing, and computer vision Growth Environment: Join an international team where your voice is heard and your impact is visible Compensation and benefits: Competitive salary package including equity, allowing you to share in the success you help build. Benefits: RRSP Plan, Health and Dental and 4 weeks holiday.

What you’ll do

Develop, deploy, and maintain production computer vision models across the full machine learning lifecycle. Optimize models for resource-constrained edge devices and establish evaluation methods to connect performance to business outcomes.

Requirements

Requires a proven track record of deploying production CV models with strong Python skills and proficiency in frameworks like PyTorch or TensorFlow. Candidates must have experience optimizing models for edge environments and applying sound software engineering practices.

Benefits

• Equity • RRSP Plan • Health Insurance • Dental Insurance • 4 Weeks Holiday

Listed skills

• Docker · Preferred
• C++ · Preferred
• Python · Preferred

Other relevant skills

Identified from the job description. Confirm important requirements above.

• Computer Vision
• Python
• PyTorch
• TensorFlow
• Scikit-learn
• CNNs
• Edge Computing
• Model Optimization
• Object Detection
• Image Classification
• Sensor Fusion
• Geospatial Tracking
• Docker
• C++
• ONNX Runtime
• TensorRT

Job areas

• Technology
• Software
• Engineering
• Data & Analytics
• Transportation