Jobs in Canada

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Added 1 month ago
Senior Agentic AI Engineer- Physical AI hub, Kitchener
Siemens
Kitchener, ON
We are seeking a Senior Agentic AI Engineer to build the harness reasoning, monitoring, recovery, and completion-gating capabilities for the Physical AI Runtime. This engineer will design…
Added 1 month ago
Machine Learning Systems and Infrastructure Developer
Siemens
Kitchener, ON
Partner with the Senior AI/ML and Robotics Platform Engineer on dataset readiness, evaluation semantics, and model-quality criteria.
Added 1 month ago
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Senior Data Engineer
TriMech
Oakville, ON
- Full-time
As Senior Data Engineer / Data Scientist, you will design, build, and operate the group's data ecosystem: integrating data from our core business systems, developing robust pipelines,…
Added 1 month ago
EA
Full Stack Software Developer
Engineered Arts
Montreal, QC
- Full-time
…welcome, supported, and empowered to contribute. Whether you’re an engineer, developer, or creative thinker, we value what makes you…
Added 1 month ago
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Intern, Developer (Winter 2027)
Bombardier
Mississauga, ON
- $17.95 to $31 CAD / hour
- Volunteer
Engineer backend automation scripts and data integration pipelines with Python and SQL, leveraging operational data to drive real-time insights and transformation on the shop floor.
Added 1 month ago
Senior Data Engineer
Quandri
Vancouver, BC
Experience in communicating with senior leadership to collect requirements, describe software product features, technical designs, and product strategy
Added 1 month ago
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Senior Data Engineer
Quandri
Vancouver, BC · Greater Vancouver Metropolitan Area
- Full-time
Experience in communicating with senior leadership to collect requirements, describe software product features, technical designs, and product strategy
Added 1 month ago
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Online Calibration & SLAM Engineer
Mecka
Richmond Hill, ON
- $200,000 to $230,000 CAD / year
- Full-time
Cross-border collaboration: You can specify calibration requirements clearly to a hardware team across time zones
Added 1 month ago
Data Analyst, Principal
Dayforce
Canada
This is a hands-on technical role with significant visibility across the organization. You will work directly with senior leaders and cross-functional stakeholders while personally…
Added 1 month ago
IE
Senior Designer, Optoelectronics
IMAX Enhanced | Streaming & Consumer Technology
Mississauga, ON
- Full-time
IMAX is seeking a Senior Optoelectronics Engineer to play a key role in the research, development, validation, and continuous improvement of next-generation entertainment technologies. This…
Added 1 month ago
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Senior Network Operations Engineer
Cognizant
Vancouver, BC
- Full-time
Job Title: Senior Network Operations Engineer
Added 1 month ago
AI
AI Developer – AI/ML, Python, LangChain, RAG, NLP LLM
Astra-North Infoteck Inc. ~ Conquering today’s challenges, achieving tomorrow’s vision!
Toronto, ON
- Full-time
What is the opportunity? The Senior AI Engineer will work on the development and deployment of cutting-edge machine learning models, drive innovation, and collaborate with cross-functional…
Added 1 month ago
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Customer Experience Engineer
Elation Health
Canada
- Full-time
…resolves the customer's problem immediately, and partner with senior engineers on the cases complex enough to need…
Added 1 month ago
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Senior Cloud Platform Engineer (AWS), AI Infrastructure - Evinova
AstraZeneca
Mississauga, ON · Canada - Mississauga
- Full-time
Candidates must reside within commuting distance of the GTA or be willing to relocate for this opportunity
Added 1 month ago
EP
Project Estimation Manager [Hybrid or Remote] - Gestionnaire Estimation des Projets [Hybride ou Télétravail] | - FR
EDF power solutions North America
Montreal, QC
- Full-time
…provide functional coverage and technical continuity for the Senior Data Solutions Engineer during periods of absence or elevated workload demand. As such, the ideal candidate will bring a…
Added 1 month ago
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Sr Full Stack AI Engineer - Calgary ,Canada (Hybrid)
Straive
Calgary, AB
- Full-time
Title - Senior Full Stack AI Engineer / Technical Engagement Manager
Added 1 month ago
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Senior Network Engineer
Kyndryl
Toronto, ON
- Contract
Provide senior-level troubleshooting, performance optimization, root cause analysis, technical documentation, and operational handover.
Added 1 month ago
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Senior Analytics Engineer – Data Modeling
SPECTRAFORCE
Toronto, ON · Greater Toronto Area, Canada
- Contract
Senior Analytics Engineer – Data Modeling (Databricks), Capital Markets
Added 1 month ago
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Senior Software Developer in Test (Development Focused)
Royal Bank of Canada
Montreal, QC
- Full-time
We are seeking a top-notch, hands on Senior Software Developer who is a passionate, driven team player committed to code quality and testing excellence. The ideal candidate will play a…
Added 1 month ago
Staff Data Infrastructure Engineer
Faire
Toronto, ON · Kitchener, ON
Specific Workplace and Information Technology positions may require onsite attendance 5 days per week as will be indicated in the job posting
Added 1 month ago
Senior Software Engineer- Generalist (Apex Legends)
Electronic Arts
Vancouver, BC
Job Title: Senior Software Engineer - Generalist (Apex Legends)
Added 1 month ago
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Machine Learning Systems and Infrastructure Developer
Siemens
Kitchener, ON
- Full-time
Partner with the Senior AI/ML and Robotics Platform Engineer on dataset readiness, evaluation semantics, and model-quality criteria.
Added 1 month ago
St Staff R&D Engineer
Synopsys
Waterloo, ON
…Full stack development is second nature to you: you design Python backends, build Angular frontends, and understand exactly where the boundaries should be and why they matter. When…
Added 1 month ago
Machine Learning Engineer - EA SPORTS™ FC
Electronic Arts
Vancouver, BC
Reporting to the Senior Data Science Manager, we are seeking a full-stack Machine Learning Engineer to operationalize, deploy, and scale high-impact machine learning solutions and…
Added 1 month ago
AI Engineer Intern
Electronic Arts
Vancouver, BC
As a Software Engineer with expertise in AI/ML systems and platform development, you will help create a scalable AI Platform.

Siemens

Machine Learning Systems and Infrastructure Developer

Kitchener, ON, Canada

Full-time

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Job details

Job type: Full-time
Experience: 3+ years of Strong experience building ML platforms, training infrastructure, MLOps systems, model lifecycle tooling, or production AI infrastructure.
Posting language: English
Posted: Oct 1, 2026

Original job description

Change the future with us.

We are looking for dedicated and talented people who solve ever-changing challenges, customer needs, and questions from colleagues with clever concepts and creativity. We embrace change and work with curious minds re-inventing the future of work. Join us and let us focus together on what’s truly important: making lives better with new ideas and the latest technology around the world.

About the role:

Are you excited by the engineering work that turns model development into repeatable, governed production rollout?

Do you enjoy building the infrastructure behind training jobs, GPU environments, experiment tracking, model registries, evaluation gates, and controlled deployment of robotics AI models?

We are seeking a Machine Learning Systems and Infrastructure Developer to build the training infrastructure and model rollout layer for Physical AI. This developer will provision and operate ML environments, automate training and evaluation pipelines, manage model artifacts and registries, and define the promotion path from trained model to validated runtime candidate. The role connects robotics data, partner VLA/RFM work, model evaluation, release gates, and runtime deployment without owning robotics data semantics or the final runtime integration layer alone.

What will you do?

Provision and maintain ML training environments for robotics AI workloads across local, edge, on-premise, and cloud-backed infrastructure where applicable.
Build repeatable training, fine-tuning, evaluation, and model-packaging pipelines for VLA, VLM, perception, and robot-learning workflows.
Manage model artifacts, model registries, dataset references, experiment metadata, lineage, approvals, promotion states, and rollback paths.
Automate GPU resource allocation, job scheduling, environment reproducibility, dependency management, and capacity tracking.
Define model rollout workflows from training output to validated runtime candidate, including evaluation gates, release notes, traceability, and operational handoff.
Partner with the Senior AI/ML and Robotics Platform Engineer on dataset readiness, evaluation semantics, and model-quality criteria.
Partner with ML inference, Edge Runtime, AX integration, QA, and DevOps engineers on packaging, deployment readiness, observability, and release automation.

What you will bring:

Bachelor's or Master's degree in Computer Science, Machine Learning, Robotics, Computer Engineering, Software Engineering, Electrical Engineering, or a related field.
3+ years of Strong experience building ML platforms, training infrastructure, MLOps systems, model lifecycle tooling, or production AI infrastructure.
Strong programming skills in Python and practical experience with containers, Linux, automation, APIs, configuration management, and reproducible environments.
Experience with training orchestration, job scheduling, GPU provisioning, artifact management, experiment tracking, model registries, or release pipelines.
Practical experience with ML frameworks and infrastructure such as PyTorch, Hugging Face tooling, Ray, Kubernetes, Slurm, MLflow, Weights & Biases, Docker, CUDA, or comparable systems.
Understanding of GPU capacity, storage, networking, data locality, dependency isolation, cost controls, and failure recovery for training workloads.
Experience connecting datasets, metadata, evaluation outputs, model artifacts, and deployment packages through traceable workflows.
Ability to define model promotion and rollback processes with clear gates for quality, reproducibility, security, and runtime readiness.
Experience partnering with data engineering, ML research, robotics, DevOps, QA, and runtime teams to make model development operational.
Strong troubleshooting skills across training jobs, data access, dependencies, GPU infrastructure, model artifacts, and rollout automation.

What sets you apart:

Experience with VLA, VLM, robotic foundation models, robot learning, imitation learning, reinforcement learning, or multimodal training workflows.
Experience operating GPU clusters, shared training platforms, high-volume data pipelines, or hybrid on-premise and cloud ML infrastructure.
Experience with distributed training, multi-node GPU workloads, or training orchestration frameworks such as Ray, Slurm, Kubernetes, Kubeflow, or comparable systems.
Experience designing portable ML infrastructure across on-premise, cloud, or multicloud environments, including data locality, reproducibility, access control, and cost management.
Familiarity with dataset versioning, data lineage, model cards, evaluation reports, approval workflows, and audit-ready model release practices.
Experience with NVIDIA tooling, CUDA environments, distributed training, model export, quantization handoff, or edge-deployment preparation.
Knowledge of governance concerns for robotics AI models, including reproducibility, traceability, fallback versions, data provenance, and release accountability.
Ability to separate training infrastructure ownership from robotics data semantics, runtime inference optimization, and industrial platform integration.
Strong judgment about when a model is ready to leave experimentation and enter controlled runtime validation.

Work Environment:

This role is primarily focused on software and infrastructure, with close collaboration across robotics data, ML research, QA, DevOps, edge runtime, and platform integration teams.
Hybrid work is supported, with on-site presence expected for training environment setup, model rollout validation, data pipeline integration, and reference-cell release readiness.

Salary is commensurate with experience, and ranges between $ 90,000 CAD- $ 140,000 CAD, excluding bonus and benefits. In addition to base salary, this role includes eligibility for an annual discretionary bonus of 10% of base salary, based on Company performance metrics. 

Why Join Us?

Impact: Build the founding team and platform capability for a strategic Physical AI initiative in Canada.
Innovation: Work at the intersection of robotics, AI, industrial software, workflow orchestration, and platform engineering.
Leadership: Shape the direction, culture, and operating model of a new strategic engineering organization.
Collaboration: Partner with leading global research, product, and engineering teams.
Growth: Help define how Physical AI platform capabilities scale from data foundations to runtime-enabled industrial applications.

Why you’ll love working for Siemens!

Freedom and a healthy work- life balance– Embrace our flexible work environment with flex hours, telecommuting and digital workspaces.
Solve the world’s most significant problems – Be part of exciting and innovative projects.
Engaging, challenging, and fast evolving, cutting edge technological environment.
Opportunities to advance your career and mentorship programs on a local and global scale.
Competitive total rewards package.
Profit sharing available.
Rewarding vacation entitlement with the opportunity to buy and sell your vacation depending on your lifestyle.
Contribute to our social responsibility initiatives focused on access to education, access to technology and sustaining communities and make a positive impact on the community.
Participate in our celebrations, social events and offsite business events.
Opportunities to contribute your innovative ideas and get paid for them!
Employee perks and discounts.
Diversity and inclusivity focused.

Siemens is proud to be an eight-time award winner of Canada’s Top 100 Employers, Canada’s Greenest Employers 2025 and Canada’s Top Employers for Young People 2025.

About Us.

We share our ideas and champion the people behind them.

Siemens Canada is a leading technology company focused on industry, infrastructure, mobility and healthcare. The company’s purpose is to create technology with purpose, transforming the everyday, for everyone, since 1912. By combining the real and the digital worlds, Siemens empowers its customers to accelerate their digital and sustainability transformations, making factories more efficient, cities more liveable, and transportation more sustainable. Siemens also owns a majority stake in the publicly listed company Siemens Healthineers, a leading global medical technology provider pioneering breakthroughs in healthcare. For everyone. Everywhere. Sustainably.

In fiscal 2024, which ended September 30, 2024, Siemens Canada had revenues of approx. $2.2 billion CAD. The company has approximately 4,400 employees from coast-to-coast and 37 office and production facilities across Canada.

To learn more about Siemens Canada, visit our website at www.siemens.ca

While we appreciate all applications we receive, we advise that only candidates under consideration will be contacted.

Canada

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More about this job

Responsibilities

Build and operate machine-learning training infrastructure and repeatable pipelines for robotics AI, including GPU resources, experiment tracking, model artifacts, registries, and evaluation. Define traceable model promotion, validation, deployment-readiness, and rollback workflows in collaboration with robotics, ML, runtime, QA, and DevOps teams.

Requirements

Requires a bachelor's or master's degree in a relevant technical field and at least three years of experience building ML platforms, training infrastructure, MLOps systems, or production AI infrastructure. Candidates should have strong Python and Linux skills, practical experience with containers and ML infrastructure tools, and knowledge of GPU workloads, reproducible environments, model lifecycle workflows, and release governance.

Skills

Python
Machine Learning Infrastructure
MLOps
Training Orchestration
GPU Provisioning
Model Lifecycle Management
PyTorch
Kubernetes
Slurm
Ray
MLflow
Docker
CUDA
Experiment Tracking
Model Registries
Distributed Training

Benefits

Annual Discretionary Bonus
Flexible Work Environment
Flexible Hours
Telecommuting
Career Advancement Opportunities
Mentorship Programs
Profit Sharing
Vacation Purchase And Sale Options
Social Responsibility Initiatives
Social And Business Events
Employee Perks And Discounts

Visa sponsorship

Not detected in the job text

Keywords

Physical AI
Robotics AI
Machine Learning Infrastructure
MLOps
Python
PyTorch
Hugging Face
Ray
Kubernetes
Slurm
Kubeflow
MLflow
Weights & Biases
Docker
Linux
CUDA
GPU Provisioning
Distributed Training
Training Orchestration
Experiment Tracking
Model Registries
Model Lifecycle Management
Model Evaluation
Model Packaging
Dataset Versioning
Data Lineage
VLA
VLM
Robot Learning
Edge Deployment

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Work requirements

Jobs in Canada