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Added 2 hours ago
Senior Dotnet Developer
Tekshapers
Toronto, ON
Full-time
Collaborate with business analysts, architects, QA teams, and stakeholders.
Added 2 hours ago
Quality Assurance Automation Engineer
Apptoza Inc.
Toronto, ON
Contract
We are seeking a QA Automation Engineer with strong expertise in Playwright to design, develop, and maintain scalable automated testing frameworks.
Added 3 hours ago
QA Test Engineer (Cloud Migration Validation, Failure Triage & Root-Cause Analysis)
Next Pathway
Toronto, ON
Full-time
Document defects with clear evidence, root-cause findings, ownership, impact, and recommended next actions; identify recurring patterns and improve test coverage and automation.
Added 3 hours ago
Jira Service Management Intake & Automation Developer : Toronto, ON (Hybrid): FTE
AceStack
Toronto, ON
Full-time
We are seeking a Jira Service Management Intake & Automation Developer to design, develop, and enhance enterprise intake, workflow, automation, and integration solutions. The ideal…
Added 3 hours ago
Senior Java Low Latency Developer with experience in Payments and Trading Platforms
K&K Global Talent Solutions INC.
Mississauga, ON
Full-time
This position is with one of our clients in Canada, who is actively hiring candidates to expand their teams.
Added 3 hours ago
Senior Java Low Latency Developer
K&K Global Talent Solutions INC.
Mississauga, ON
Full-time
…platforms. This role is ideal for a highly skilled engineer with a strong background in low-latency trading systems, financial markets technology, and modern Java…
Added 4 hours ago
Jira Service Management Intake & Automation Developer / Toronto, ON (Onsite) - FTE
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Toronto, ON
Full-time
We are seeking a Jira Service Management Intake & Automation Developer to design, develop, and enhance enterprise intake, workflow, automation, and integration solutions. The ideal…
Added 4 hours ago
Automation Test Engineer
Triunity Software, Inc.
Toronto, ON
$90,000 to $120,000 CAD / year
Full-time
Drive automation framework design, tool selection, and coverage roadmap in partnership with automation engineers.
Added 4 hours ago
Quality Engineer I
TD
Toronto, ON
Full-time
As a candidate, you are encouraged to ask compensation related questions and have an open dialogue with your recruiter who can provide you more specific details for this role.
Added 5 hours ago
Python Full Stack Engineer - Professional
HEXAWARE
Canada
Full-time
Java and Python We are seeking a skilled Backend Developer with 5 to 8 years of experience in designing, developing, and maintaining scalable backend applications. The ideal candidate will…
Added 5 hours ago
Technical Scrum Master
INFOYA
Toronto, ON
$85,000 to $90,000 CAD / year
Full-time
Understanding of DevOps practices, test automation, and quality gates; 3+ years working with QA or quality engineering teams.
Added 5 hours ago
Quality Assurance Engineer - Physical AI hub, Kitchener
Siemens
Kitchener, ON
Experience with test automation frameworks such as PyTest, Robot Framework, Playwright, Selenium, CI/CD test runners, simulation frameworks, or HIL test orchestration tools.
Added 5 hours ago
Machine Learning Systems and Infrastructure Developer
Siemens
Kitchener, ON
Partner with ML inference, Edge Runtime, AX integration, QA, and DevOps engineers on packaging, deployment readiness, observability, and release automation.
Added 11 hours ago
Développeur(euse) en assurance qualité logicielle - Software Quality Assurance Developer
Eaton Corporation
Brossard, QC
Full-time
Experience with test automation tools (e.g., Cypress, Test Complete, SOAPUI, Postman).
Added 12 hours ago
Quality Assurance - Vice President
iCapital
Toronto, ON · Greater Toronto Area, Canada
Full-time
…world-class quality organization. This position partners closely with product, engineering, and security leaders to embed quality throughout the software development lifecycle and align QA…
Added 12 hours ago
Senior QA Engineer – Mobile Testing (Field Mobility)
W3Global
Canada
Full-time
The role requires a strong combination of manual testing, mobile automation, API testing, and cross-functional collaboration with great communication and collaboration skills.
Added 16 hours ago
Software Developer II
LMI Technologies
Burnaby, BC
$93,000 to $139,000 CAD / year
Full-time
…Proactively explore and collaborate across adjacent domains - working with Front-End (UI/UX) developers, Vision Engineers, and QA automation teams to ensure seamless full-stack integration…
Added 16 hours ago
Senior Java Full Stack Developer
CGI
Toronto, ON
Full-time
We are looking for a Full Stack Developer with hands-on expertise in both Angular-based front-end development and Java/Spring-based back-end development, along with demonstrated experience…
Added 18 hours ago
SDET with Java
PEOPLE FORCE CONSULTING INC
Quebec, QC
Contract
We are seeking a Senior SDET (Software Development Engineer in Test) with strong expertise in Java, Spring Boot, and modern test automation practices to support a large-scale QA…
Added 19 hours ago
Software Developer II
LMI Technologies
Burnaby, BC
$93,000 to $139,000 CAD / year
Full-time
…Proactively explore and collaborate across adjacent domains - working with Front-End (UI/UX) developers, Vision Engineers, and QA automation teams to ensure seamless full-stack integration…
Added 20 hours ago
Executive Quality
Aptino, Inc.
Toronto, ON
$35 to $40 CAD / hour
Contract
We are looking for a Tosca QE Sr Analyst with strong experience in QA automation, backend testing, and quality engineering.
Added 21 hours ago
Quality Analyst with TOSCA
Experis Canada
Toronto, ON
Contract
Support AI application testing and modern automation practices
Added 21 hours ago
Sr SDET
Tata Consultancy Services
Toronto, ON
$90,000 to $110,000 CAD / year
Full-time
…clients, its investors, its employees, and the community at large. With a highly skilled workforce spread across 56 countries and 194 service delivery centers across the world, the company…
Added 21 hours ago
Software Architect - AI-Enabled Engineering
Wärtsilä
Vancouver, BC
This role combines hands-on software development with technical leadership and a strong focus on introducing and scaling AI-assisted engineering practices across the software development…
Added 22 hours ago
Java Software Release Engineer w Cybersecurity Expertise
Agnovi Corporation
Ottawa, ON
Full-time
Experience with CI/CD pipelines, build automation tools (e.g., Maven, Gradle), and source control systems (e.g., Git).

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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