Machine Learning Engineer

Invision AI; Toronto; Hybrid; CAD 110,000 - 150,000; Full time

Benefits offered by this job

Equity

RRSP Plan

Health and Dental

4 weeks holiday

Job summary

Invision AI in Toronto seeks a Machine Learning Engineer to develop, deploy, and maintain production computer vision models for edge devices. You will contribute across data collection, labeling, training, evaluation, deployment, and monitoring in a fast-paced environment.

The role emphasizes building accurate, efficient CV systems and collaborating with software, product, and other engineering teams to advance our ML practices.

Qualifications

• Proven track record developing production CV models.
• Strong Python software development skills.
• Experience with PyTorch, TensorFlow, scikit-learn.
• Hands-on with CNNs and modern CV architectures.
• Ability to adapt open-source models to product needs.
• Optimize models for edge devices (latency, memory).
• Experience in experiment tracking and dataset versioning.
• Knowledge of model monitoring and production troubleshooting.

Responsibilities

• Develop, evaluate, deploy ML models across product lines.
• Improve data-labeling, training, and evaluation pipelines.
• Establish evaluation methods linking model performance to business outcomes.
• Prototype new product capabilities using appropriate technologies.
• Optimize models for edge latency, memory, power, accuracy.
• Diagnose issues in deployed models and retrain as needed.
• Monitor production performance and detect model drift.

Skills

Python

PyTorch

TensorFlow

scikit-learn

CNNs

edge AI

model deployment

system performance

Tools

Docker

ONNX Runtime

TensorRT

Job description

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

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.