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Added 54 mins ago
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Technician - Mississauga, ON
Intertek
Mississauga, ON
- Full-time
Obtaining and recording test data in accordance with the product standards
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- Full-time
Company, Department: Nova Scotia Power, IT Project Management Office
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Added 55 mins ago
NT
Intermediate Machine Learning Developer
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- Full-time
Prototype and test new features against the applied research roadmap defined by senior engineering.
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Student Intern, IT Business Application Development
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- $65,000 to $75,000 CAD / year
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Novarc Technologies Inc.

Intermediate Machine Learning Developer

Vancouver, BC, Canada
Greater Vancouver Metropolitan Area, Canada

Full-time

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Job details

Job type: Full-time
Apply by: Dec 9, 2026
Experience: 3+ years of practical experience with PyTorch, TensorFlow, and OpenCV.
Posting language: English
Posted: Nov 9, 2026

Original job description

Role Summary:

Our never-before-seen, adaptive welding products push the limit of what physical AI in general, and machine learning in particular, can do today. We are looking for an experienced and hands-on Intermediate Machine Learning Developer to join our growing team and support existing products and help us develop new ones.

As an Intermediate Machine Learning Developer, reporting to the Development Manager, AI/Robotics, you will be responsible for building and deploying perception, classification, segmentation, and AI capabilities for our NovAI intelligence suite. Working with senior ML engineers, you will own the implementation of models and production pipelines!

Key Responsibilities :

- Model Development & Research

Build, train, and evaluate computer vision/ML models (detection, segmentation, tracking, pose estimation, image fusion) using PyTorch and TensorFlow.
Fine-tune neural network architectures (CNN, RNN, Transformer) and classical ML methods for real-time welding process sensing.
Prototype and test new features against the applied research roadmap defined by senior engineering.
Implement vision-language-action (VLA) models and foundation architectures for spatial reasoning and multi-modal perception.
Develop and integrate world models for predictive perception, spatial reasoning, and dynamic environmental simulation in adaptive welding scenarios.
Develop closed-loop reinforcement learning (RL), imitation learning, and continuous learning policies for complex control tasks, adaptive manipulation, and robotic feedback loops.
Architect simulation-to-real (Sim2Real) pipelines and synthetic data workflows (Isaac Gym, MuJoCo) to accelerate domain randomization.

- Physical AI & Robotics Integration

Fuse vision, arc, and thermal sensor data to enable real-time robotic decision-making.
Integrate ML outputs with motion control, PLCs, and robot controllers within target latency, power, and compute budgets.
Support toolpath and trajectory optimization for stress reduction, energy efficiency, and faster cycle times.

- Deployment, Testing & MLOps

Optimize models for real-time edge implementation and maximize hardware efficiency using quantization, pruning, TensorRT, and ONNX Runtime on embedded platforms.
Validate and troubleshoot end-to-end integrations across software and hardware stack components.
Maintain state machine documentation, architecture diagrams, technical specifications, and user guides.
Provide onsite and remote commissioning support during customer installations.
Implement robust MLOps practices, including automated model versioning, validation workflows, and monitoring (W&B/MLflow).

- Cross-Functional Collaboration

Partner with controls and welding engineering teams to integrate robotic systems with external automation hardware.
Contribute to scientific publications and patent applications; evaluate emerging ML tooling and frameworks.
Travel as required to customer deployment sites or industry conferences.

Qualifications and Experience :

Bachelor's degree in CS, Electrical Engineering, Software Engineering, or related field (Master's preferred).
3+ years of practical experience with PyTorch, TensorFlow, and OpenCV.
Strong foundation in supervised/unsupervised learning, deep neural networks (CNNs/RNNs), and transfer learning.
Solid computer vision skills: image processing, object detection, segmentation, and feature extraction.
Proficiency in C++ and Python applied to robotic systems.
Strong communication and documentation skills
Strong organizational and time management skills
Strategic, critical thinking, and analytical skills for structured problem-solving rather than band-aid fixes.

Preferred Additional Qualifications:

Experience integrating an AI pipeline with a third party PC/PLC
Hands-on exposure to edge inference optimization or Physical AI systems.
Familiarity with industrial sensing or automated welding processes.

Commitment to Novarc Values:

Demonstrate and embed Novarc’s core values of Hungry, Humble, and Smart in daily work, decision-making, collaboration, and interactions with colleagues, customers, and partners.

Hungry: Be Passionate, Never Give Up, Customer Focused, Continuous Learning, Do What You Say
Humble: Servant Leader, No arrogance, Less Ego, Listen > Talk
Smart: High EQ, Challenge the Status Quo, Thought Leaders

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More about this job

Responsibilities

Develop, train, evaluate, and deploy machine learning and computer vision models for adaptive welding products, including perception, segmentation, predictive reasoning, and robotic control capabilities. Integrate and optimize models across robotic and industrial hardware, maintain production and MLOps pipelines, support testing and customer commissioning, and collaborate with engineering teams on new capabilities.

Requirements

Requires a bachelor's degree in computer science, electrical engineering, software engineering, or a related field; a master's degree is preferred. Candidates should have at least three years of practical experience with PyTorch, TensorFlow, and OpenCV, strong computer vision and machine learning foundations, and proficiency in Python and C++ for robotic systems.

Skills

Machine Learning
Computer Vision
PyTorch
TensorFlow
OpenCV
Python
C++
Robotics
Model Deployment
Object Detection
Image Segmentation
Reinforcement Learning
Edge Inference Optimization
MLOps
Sensor Fusion
PLC Integration

Visa sponsorship

Not detected in the job text

Keywords

PyTorch
TensorFlow
OpenCV
Python
C++
Computer Vision
Machine Learning
Deep Neural Networks
CNN
RNN
Transformers
Object Detection
Image Segmentation
Tracking
Pose Estimation
Image Fusion
Vision-Language-Action Models
World Models
Reinforcement Learning
Imitation Learning
Simulation-to-Real
Isaac Gym
MuJoCo
TensorRT
ONNX Runtime
MLOps
Weights & Biases
MLflow
Robotic Control
PLC Integration

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