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Added 11 mins ago
Software Engineer
ExaCare AI
Toronto, Ontario
We are looking for a Software Engineer who is eager to grow, take ownership, and build products that solve meaningful customer problems. In this role, you will contribute to user-facing…
Added 25 mins ago
Salesforce Release Engineer
Cognizant
Toronto, ON
$78,000 to $125,000 CAD / year
Full-time
Manage pre-production and production deployment processes, including migration, business validation testing (BVT), Dynamic Application Security Testing (DAST), rollback planning, and…
Added 25 mins ago
Ingénieur en test et conception mécanique / Test & Mechanical Engineer
Wabtec Corporation
Montreal, QC
Full-time
…la conception, l’adaptation, le prototypage, les tests et la validation de produits électromécaniques complexes; pour les contrats OEM et de services avec les constructeurs ferroviaires les…
Added 25 mins ago
Principal Systems Engineer - Optical Transceivers
ConsultNet Technology Services and Solutions
Ottawa, ON
Other
Collaborate across optics, DSP, ASIC, firmware, mechanical, packaging, validation, manufacturing, and operations teams
Added 55 mins ago
Software Supply Chain Security Engineer
Actalent
Ottawa, ON · Nepean, ON
$65 to $85 CAD / hour
Contract
We are seeking a hands-on Software Supply Chain Security Engineer specializing in vulnerability management to identify, investigate, prioritize, and remediate security issues across…
Added 55 mins ago
Security Software Engineer
Actalent
Ottawa, ON
$65 to $85 CAD / hour
Contract
The Security Software Engineer designs, builds, and supports secure systems that provision sensitive information into devices during manufacturing. This role focuses on protecting…
Added 55 mins ago
Data Operations Engineer
goeasy Ltd.
Mississauga, ON
Full-time
The Data Operations Engineer is responsible for supporting, maintaining, and continuously improving goeasy's enterprise data platform. This role focuses on ensuring the reliability,…
Added 55 mins ago
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 55 mins ago
Software Engineer
Actalent
Ottawa, ON
$50 to $74 CAD / hour
Contract
Use scripting (e.g., Python) and automation to support testing, validation, and acceptance testing of BSP and OS components.
Added 55 mins ago
Jr. Product Engineer
Semtech
Burlington, ON
Full-time
We are looking for a Junior NPI Product Engineer to join our team. This role supports new product development activities - from early-stage development through production transfer - working…
Added 56 mins ago
Instrument Operator Technician (2 Month Contract)
VitalBio
Oakville, ON
Full-time
…electromechanical prototypes. This is not a passive role; it requires an engineer’s mindset to spot anomalies, a coder’s logic to automate tasks, and a scientist’s rigour regarding data…
Added 1 hour ago
Industrial Edge Integration Engineer - Physical AI hub, Kitchener
Siemens
Kitchener, ON
We are seeking an Industrial Edge Integration Engineer to help integrate the Physical AI Runtime with SIMATIC AX and Siemens Industrial Edge. SIMATIC AX is Siemens' software-defined…
Added 1 hour ago
Sr Stress Engineer
Insight Global
Mirabel, QC
$113,000 to $163,000 CAD / year
Full-time
Our client is seeking a Senior Stress Engineer for a permanent opportunity based in Mirabel, QC. This role focuses on validating aeronautical structures for both commercial and military…
Added 1 hour ago
Engineering Technician
ExcelGens, Inc.
Mississauga, ON
Contract
We are seeking a Mechanical Test Engineer / Test Technician with a Mechanical Engineering or Mechatronics background to support testing and validation of mobile computing products and…
Added 1 hour ago
OpenShift Support Engineer
Raas Infotek
Toronto, ON
Contract
We are looking for a hands-on platform engineer who:
Added 1 hour ago
RF Hardware Engineer – Design & Validation
Emtar Technologies Inc.
Richmond, BC
Full-time
…the company. We are seeking a highly adaptable RF RF Hardware Engineer – Design & Validation with expertise in board-level RF circuit design and PCB layout to join our test and validation…
Added 2 hours ago
Systems Verification & Validation Engineer
Aversan Inc.
Mill Bay, BC
$95,000 to $115,000 CAD / year
Full-time
…conducting, and reporting on IVVQ (Integration, Verification, Validation, and Qualification) activities. While standardized test scripts will be provided, the successful candidate must have…
Added 2 hours ago
Municipal Infrastructure Engineer - Closing October 16, 2026
Municipality of Port Hope
Port Hope, ON
Full-time
The Municipal Infrastructure Engineer is responsible for the review of all engineering facets of development proposals submitted to the Municipality of Port Hope, including Plans of…
Added 2 hours ago
Human Factors Engineer
AtkinsRéalis
Mississauga, ON
Full-time
Development of Human Factor Verification and Validation plans per CNSC REGDOC 2.5.1.
Added 2 hours ago
Human Factors Engineer
AtkinsRéalis
Mississauga, ON
Full-time
Development of Human Factor Verification and Validation plans per CNSC REGDOC 2.5.1.
Added 2 hours ago
Quality Engineer - 12 Months Contract
Apollo Health And Beauty Care
Toronto, ON
$80,000 to $90,000 CAD / year
Full-time
The Quality Engineer is responsible for delivering all aspects of the Operations Quality Assurance function on an on-going basis in line with the Quality Management System and Quality…
Added 2 hours ago
Telecommunications Systems Analyst
TEKsystems
Calgary, AB
$45 to $60 CAD / hour
Contract
…configurations, hunt groups, call queues, voicemail settings, validation testing, migration support, and post-cutover issue…
Added 3 hours ago
Systems Engineer (Aerospace)
Insight Global
Longueuil, QC
$35 to $45 CAD / hour
Contract
Insight Global is seeking a Systems Engineer to join a top aerospace company in Longueuil, QC. This role is 5x week onsite, with flexible hours.
Added 3 hours ago
Customer Success Manager/Engineer
Speedy Labs
Remote, Canada
$60,000 to $120,000 USD / year
Contract · Remote
Lead customer implementations: Own implementation plans from kickoff through data ingestion, configuration, validation, training, and go-live.
Added 3 hours ago
Silicon Validation/Characterization Engineer - 18757
Synopsys
Ottawa, ON
…you do not stop until you know which one. The hardest part of validation is not running the test; it is designing the test that actually tells you something…

Siemens

Machine Learning Systems and Infrastructure Developer

Kitchener, ON, Canada

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 2, 2026

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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.

Siemens is committed to creating a diverse environment and is proud to be an equal opportunity employer. Upon request, Siemens Canada will provide reasonable accommodation for disabilities to support participation of candidates in all aspects of the recruitment process. All qualified applicants will receive consideration for employment.

By submitting personal information to Siemens Canada Limited or its affiliates, service providers and agents, you consent to our collection, use and disclosure of such information for the purposes described in our Privacy Notice available at www.siemens.ca.

Siemens s’engage à créer un environnement diversifié et est fière d’être un employeur souscrivant au principe de l’égalité d’accès à l’emploi. Sur demande, Siemens Canada prendra des mesures d’accommodement raisonnables pour les personnes handicapées, dans le but de soutenir la participation des candidats dans tous les aspects du processus de recrutement. Tous les candidats qualifiés seront pris en considération pour ce poste.

En transmettant des renseignements personnels à Siemens Canada limitée ou à ses sociétés affiliées, à ses fournisseurs de services ou à ses agents, vous nous autorisez à recueillir, à utiliser et à divulguer ces renseignements aux fins prévues dans notre Déclaration de protection de la confidentialité, que vous pouvez consulter au www.siemens.ca.

Job ID

524099

Posted since

01-Oct-2026

Organization

Digital Industries

Field of work

Research & Development

Company

Siemens Canada Limited

Experience level

Experienced Professional

Job type

Full-time

Work mode

Hybrid (Remote/Office)

Employment type

Permanent

Location(s)

Kitchener - Ontario - Canada

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More about this job

Responsibilities

The developer will build and maintain infrastructure for training robotics AI models, including GPU resource management, experiment tracking, and model rollout pipelines. They will collaborate with cross-functional teams to ensure model reproducibility, scalability, and operational readiness.

Requirements

Candidates must hold a Bachelor's or Master's degree in a relevant engineering or science field and possess at least 3 years of experience in ML platform or infrastructure development. Strong proficiency in Python, containerization, and experience with ML frameworks like PyTorch or Ray is required.

Skills

Python
Machine Learning
Robotics
MLOps
Infrastructure Development
Kubernetes
PyTorch
GPU Provisioning
Docker
Slurm
Ray
Model Lifecycle Management
Automation
Linux
CI/CD
Distributed Training

Benefits

Annual discretionary bonus
Flexible work environment
Telecommuting
Digital workspaces
Mentorship programs
Profit sharing
Vacation entitlement
Employee perks and discounts
Social responsibility initiatives

Visa sponsorship

Not detected in the job text

Keywords

Machine Learning
Robotics
Infrastructure
MLOps
Physical AI
Python
Kubernetes
PyTorch
Ray
Slurm
Docker
CUDA
GPU
Model Registry
Automation
CI/CD
VLA
VLM
Perception
Data Lineage
Observability
DevOps
Cloud Infrastructure
On-premise
Distributed Training
Model Lifecycle
Software Engineering
Robotic Foundation Models
Governance
Traceability

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