Senior, Machine Learning Engineer - Camera Model

Job summary

You will design, develop, and deploy deep learning models for camera-based perception to power autonomous trucks. This involves owning the end-to-end model development lifecycle, from data curation and training to evaluation and production deployment.

Job details

About the Company At Torc, we have always believed that autonomous vehicle technology will transform how we travel, move freight, and do business. A leader in autonomous driving since 2007, Torc has spent over a decade commercializing our solutions with experienced partners. Now a part of the Daimler family, we are focused solely on developing software for automated trucks to transform how the world moves freight. Join us and catapult your career with the company that helped pioneer autonomous technology, and the first AV software company with the vision to partner directly with a truck manufacturer. Meet the Team As a Senior Machine Learning Engineer – Camera Models, you will develop and deploy machine learning models that power camera-based perception for autonomous trucks. The Camera Models team builds and maintains core vision systems that enable the autonomy stack to understand the environment, detect and localize objects, and estimate scene structure from camera data. Working closely with teams across perception, data, and infrastructure, you will own the development and improvement of robust, scalable camera-based models that support safe and reliable autonomous driving in real-world freight environments. This role focuses on owning model development for scoped problem areas, improving system performance through iteration, and delivering production-ready machine learning solutions within the autonomy stack. What You’ll Do Design, develop, and deploy deep learning models for camera-based perception (e.g., object detection, segmentation, depth estimation, scene understanding) Own end-to-end model development for scoped areas, from data curation and training to evaluation and deployment Write production-quality ML code to support scalable training, evaluation, and inference pipelines Analyze model performance across diverse driving scenarios, identify failure modes, and improve robustness and generalization Contribute to and improve large-scale training pipelines, including dataset preparation, distributed training, and experiment tracking Partner with data teams to improve dataset quality, including labeling strategies and coverage of edge cases Collaborate with perception, simulation, and validation teams to evaluate and integrate models into the autonomy stack Improve tooling, workflows, and infrastructure to accelerate experimentation and model iteration Contribute to model architecture decisions and technical discussions within the team Mentor junior engineers on implementation, debugging, and best practices What You’ll Need to Succeed Bachelor’s degree in Computer Science, Robotics, Electrical Engineering, Machine Learning, or a related technical field with 6+ years of industry experience, OR Master’s degree with 3+ years OR PhD with 1+ years of experience Experience developing and deploying deep learning models for computer vision or perception systems Strong programming skills in Python and PyTorch, with experience writing production-quality ML code Experience training and evaluating models using large-scale datasets and distributed compute environments Solid understanding of modern deep learning architectures used in perception (e.g., CNNs, transformers, multi-task models) Experience debugging model behavior, analyzing performance metrics, and improving model reliability Ability to translate ambiguous problems into structured ML solutions and deliver independently Experience collaborating cross-functionally to integrate ML models into larger autonomy or robotics systems Bonus Points: Experience in autonomous driving, robotics, or simulation-based ML systems Experience with multi-task learning or unified perception architectures Experience with large-scale data pipelines, distributed training systems (e.g., Ray), or experiment management frameworks Familiarity with camera calibration, geometric reasoning, or 3D perception from images (e.g., BEV, monocular depth, structure-from-motion) Experience deploying ML models into production or real-world robotics systems Work Location: For this position, we are open to hiring in Montreal, Canada or remote within Canada Perks of Being a Full-time Torc’r (Canada) Torc cares about our team members and we strive to provide benefits and resources to support their health, work/life balance, and future. Our culture is collaborative, energetic, and team focused. Torc offers: A competitive compensation package that includes a bonus component and stock options Medical, dental, and vision for full-time employees RRSP plan with a 6% employer match Public Transit Subsidy (Montreal area only) Flexibility in schedule and generous paid vacation Company-wide holiday office closures Life Insurance At Torc, we’re committed to building a diverse and inclusive workplace. We celebrate the uniqueness of our Torc’rs and do not discriminate based on race, religion, color, national origin, gender (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender identity, gender expression, age, veteran status, or disabilities. Even if you don’t meet 100% of the qualifications listed for this opportunity, we encourage you to apply. Our compensation reflects the cost of labor across several geographic markets. Pay is based on a number of factors and may vary depending on job-related knowledge, skills, and experience. Torc's total compensation package will also include our corporate bonus and stock option plan. Dependent on the position offered, sign-on payments, relocation, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. Job ID: 102952 Salary Range: $168,000-$193,000 CAD

What you’ll do

You will design, develop, and deploy deep learning models for camera-based perception to power autonomous trucks. This involves owning the end-to-end model development lifecycle, from data curation and training to evaluation and production deployment.

Requirements

Candidates must have a degree in a technical field with 1-6+ years of industry experience depending on the degree level. Proficiency in Python, PyTorch, and experience with deep learning for computer vision or perception systems is required.

Benefits

• Medical insurance
• Dental insurance
• Vision insurance
• RRSP plan with 6% employer match
• Public transit subsidy
• Paid vacation
• Company-wide holiday office closures
• Life insurance
• Bonus component
• Stock options

Listed skills

• Machine learning · Preferred
• Python · Preferred

Other relevant skills

Identified from the job description. Confirm important requirements above.

• Machine learning
• Computer vision
• Python
• PyTorch
• Deep learning
• Object detection
• Segmentation
• Depth estimation
• Scene understanding
• Distributed training
• Perception systems
• Autonomous driving
• Model deployment
• Data curation
• Robotics
• Management
• Reliability
• Tooling
• Workflow Management
• Electrical Engineering
• Pipelines
• Machine Learning
• Data Pipelines
• Python (Programming Language)
• Energetic
• Scalability
• Computer Science
• Business Metrics
• Performance Metric
• Debugging
• Multitasking
• Computer Vision
• Simulations
• PyTorch (Machine Learning Library)
• Packaging And Labeling
• Experimentation
• Workplace Inclusivity
• Failure Causes
• Machine Learning Model Monitoring And Evaluation
• Object Detection
• Transformer (Machine Learning Model)
• Autonomous Vehicles
• Deep Learning
• Course Evaluations
• Public Transport
• Distributed Machine Learning
• Model Architecture
• Data Curation
• Camera Calibration
• Scene Understanding

Job areas

• Technology
• Software
• Engineering
• Data & Analytics
• Transportation
• Machine Learning Engineer
• Software Developers
• Computer and Information Research Scientists

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