Jobs in Canada

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Added 1 month ago
Project Engineer, Intermediate
Lakeside Controls
Mississauga, ON
Lakeside Process Controls Ltd. (‘Lakeside’) is recognized as a market leader, providing complete automation solutions to a wide range of industries. Our capabilities in process management…
Added 1 month ago
Project Engineer, Senior
Lakeside Controls
Sarnia, ON
Lakeside Process Controls Ltd. (‘Lakeside’) is recognized as a market leader, providing complete automation solutions to a wide range of industries. Our capabilities in process management…
Added 1 month ago
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Automation & Controls Engineer III
Anaergia
Burlington, ON
- Full-time
The Automation & Controls Engineer III is a senior individual contributor who independently leads the technical delivery of industrial automation and process control systems throughout the…
Added 1 month ago
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Instrumentation and Control Engineer Part-Time Contractor (15-20 hrs/week)
VulcanX
AB · Calgary, Alberta
- Part-time
- Contract
We are seeking an experienced part-time Instrumentation and Control Engineer (15-20 hrs/week) to join our dynamic team and support the FEED, detailed design, procurement, construction,…
Added 1 month ago
AM
Sr. Director, Total Rewards
Array Marketing
Toronto, ON · Scarborough, Ontario
- Full-time
…Sephora, L’Oréal, Coty, PUIG, Amazon, and many others to design, engineer, manufacture, and deliver bespoke retail environments that bring their brands to…
Added 1 month ago
TT
Senior Project Coordinator
Torus Talent
AB · Greater Edmonton Metropolitan Area
- Full-time
Support cost control and quantity tracking, ensuring alignment with cost codes and internal reporting systems.
Added 1 month ago
A
C1R EPC Retube Project Director
AtkinsRéalis
Mississauga, ON
- Full-time
…procurement, construction management, contract management and project controls…
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
A
C1R EPC Retube Project Director
AtkinsRéalis
Mississauga, ON
- Full-time
…procurement, construction management, contract management and project controls…
Added 1 month ago
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Platform/DevOps Engineer
Vasco
Remote, Canada
- Full-time
- Remote
Security and compliance: Own data security and access for systems that hold customer revenue data (IAM, secrets, network controls, Cloudflare, Aikido, model inference), with least privilege…
Added 1 month ago
LP
Project Engineer, Automation, Senior
Lakeside Process Controls
Winnipeg, MB
- $95,000 to $120,000 CAD / year
- Full-time
Lakeside Process Controls Ltd. (‘Lakeside’) is recognized as a market leader, providing complete automation solutions to a wide range of industries. Our capabilities in process management…
Added 1 month ago
Project Engineer, Automation, Intermediate
Lakeside Controls
Winnipeg, MB
Lakeside Process Controls Ltd. (‘Lakeside’) is recognized as a market leader, providing complete automation solutions to a wide range of industries. Our capabilities in process management…
Added 1 month ago
SE
Senior Systems Administrator
S&C Electric Company
Toronto, ON · Etobicoke, ON
- Full-time
The Senior Systems Administrator, Identity is responsible for the secure administration, support, and continuous improvement of the organization’s identity and access management…
Added 1 month ago
08 - Lead Engineer, Systems/Applications Design
Celestica International LP
Newmarket, ON
Must possess a Machinist Certification issued by Skilled Trades Ontario
Added 1 month ago
Senior Gameplay Software Engineer - EA SPORTS™ NHL
Electronic Arts
Vancouver, BC
We are looking for an experienced Senior Gameplay Engineer to join our team in Vancouver and help craft the next generation of on-ice gameplay. In this role, you will be a core architect of…
Added 1 month ago
Senior Gameplay Software Engineer - EA SPORTS™ UFC
Electronic Arts
Vancouver, BC
We are looking for a passionate and talented Senior Gameplay Engineer to help shape the core player experience and elevate our combat systems to the next level. In this role, you will be a…
Added 1 month ago
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Machine Learning Systems and Infrastructure Developer
Siemens
Kitchener, ON
- Full-time
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…
Added 1 month ago
Gameplay Software Engineer - EA SPORTS™ FC
Electronic Arts
Vancouver, BC
Design and write the code that runs and controls the game, incorporating and adapting existing libraries and writing custom code
Added 1 month ago
B&
Facility Supervisor
Black & McDonald Limited
Ottawa, ON
- $75,000 to $85,000 CAD / year
- Full-time
Candidates possessing a Stationary Engineer certification with extensive mechanical systems experience and demonstrated troubleshooting capability will also be considered.
Added 1 month ago
JC
26-OTT06 - Intermediate Electrical Engineer or Technologist- Ottawa
Jp2g Consultants Inc.
Ottawa, ON
- Full-time
Our growing Ottawa office currently requires an Intermediate Electrical Engineer or Technologist. The ideal candidate is diligent, hardworking, and team oriented.
Added 1 month ago
MD
Senior Systems / Cloud Engineer
Minnesota Direct Care and Treatment
Saint-Paul, NB · St.-Paul, NB
- Full-time
Work Shift/Work Hours: Day Shift
Added 1 month ago
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Solutions Consultant
Procurify
Remote, Canada
- Full-time
- Remote
Conduct technical scoping for both out-of-the-box integrations and custom API integrations to client ERP and accounting systems (e.g., NetSuite, Sage Intacct, Microsoft Dynamics,…
Added 1 month ago
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Director of Technology / Directeur ou directrice de la technologie
FENCECORE
Montreal, QC
- Full-time
Added 1 month ago
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Senior Applied AI Engineer – GenAI & Actuarial Systems
Manulife
Toronto, ON
- Full-time
Translate business problems into a clear solution approach: business workflow, data flow, modeling approach, evaluation plan, and operational controls.
Added 1 month ago
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Applied AI Engineer – GenAI Systems
Manulife
Toronto, ON
- Full-time
…for governance teams to review with evidence, testing, and controls. If you enjoy turning ambiguous business problems into clear system designs, strong evaluations, and reliable production…

Siemens

Machine Learning Systems and Infrastructure Developer

Kitchener, ON, Canada

Full-time

Apply on LinkedIn About employer

Applications open in a new tab.

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

Apply on LinkedIn About employer

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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Jobs in Canada