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Added 17 days ago
Senior Forward-Deployed AI Engineer 1
Bell
Toronto, ON
As a Senior Forward-Deployed AI Engineer, you will own engagements end-to-end: scoping the problem, choosing the right approach across automation, classical ML, and GenAI/agents, and taking…
Added 17 days ago
A
Senior Machine Learning Engineer
Autodesk
Toronto, ON · AMER - Canada - Ontario - Toronto - University Ave
- Full-time
We are looking for an exceptional Machine Learning Engineer to design, build, operationalize, and scale production-grade AI/ML and Agentic AI systems at Autodesk For Go-to-market…
Added 17 days ago
Senior Product Solutions Analyst
Scotiabank
Toronto, ON
Strong understanding of classical machine learning, model development, MLOps, and generative AI
Added 18 days ago
RB
Senior AI/ML Engineer
Royal Bank of Canada
Toronto, ON
- Full-time
Proficiency in programming languages such as Python, with experience in machine learning libraries (e.g., TensorFlow, PyTorch).
Added 18 days ago
HD
Databricks Engineer
Hire DigITalent Inc.
Toronto, ON · Greater Toronto Area, Canada
- $90 to $110 CAD / hour
- Contract
…marketing and promotions. The project team needs a seasoned Senior Data Engineer to help lead the charge, stabilize key deliverables, and guide our technical strategy. This is a critical…
Added 18 days ago
M-
Développeur Logiciel Principal.e, Plan de Contrôle - Laboratoire d'IA Souveraine
Mila - Institut québécois d'intelligence artificielle
Montreal, QC
- Full-time
As Staff Software Engineer, Control Plane, you will own the software through which administrators configure, govern, and understand the assembled stack. Reporting to the Senior Director of…
Added 19 days ago
S
Senior DevOps Engineer – AI & Data Platform
Systematix
Canada
- Contract
Partner with MLOps engineers to automate machine learning lifecycle, deployment and operational processes.
Added 19 days ago
A
Senior AI Platform Engineer (MLOps)
Akkodis
Toronto, ON
- Contract
Akkodis is partnering with a leading institutional investment and pension organization to engage an experienced Senior AI Platform Engineer (MLOps) to support the ongoing growth and…
Added 19 days ago
AI Engineer
Bell
Toronto, ON
…autonomous agentic workflows, conversational intelligence, and machine learning systems that transform our internal operations and customer…
Added 19 days ago
T
AVP, Analytics, Insights and AI, AI Product
TD
Toronto, ON
- Full-time
…performance-manage direct reports; build succession; align senior business, technology and control partners; remove barriers and raise product…
Added 21 days ago
H
Senior Software Engineer, Machine Learning
hive.co
Remote, Canada
- Full-time
- Remote
As a Senior Data Engineer, you’ll play a vital role in evolving our data platform, which directly determines what our customers can do, how fast our product moves, and how confidently…
Added 22 days ago
R
Senior Director, Program Delivery
RBC
Toronto, ON
- Full-time
As a member of RBC Borealis AI, reporting to the VP, Solutions Engineering & Delivery, the Senior Director, Program Delivery will lead the strategic planning, execution, and governance of…
Added 22 days ago
R
Senior AI/ML Engineer
RBC
Toronto, ON
- Full-time
Proficiency in programming languages such as Python, with experience in machine learning libraries (e.g., TensorFlow, PyTorch).
Added 22 days ago
DI
MLOps Engineer – Databricks (1896) $90-100hr
Direct IT Recruiting Inc.
Toronto, ON
- $90 to $100 CAD / hour
- Contract
Define and operationalize the AI delivery model, including reusable implementation patterns, reference solutions, and engineering standards for RAG, agentic, and machine learning solutions.
Added 22 days ago
WT
Senior Software Developer, ML Platform & Infrastructure
Wealthsimple Technologies
Toronto, ON
- $152,000 to $189,000 CAD / year
- Full-time
The Machine Learning Infrastructure & Platform team builds the foundational architecture powering AI and GenAI initiatives across Wealthsimple. We sit at the intersection of production…
Added 23 days ago
Machine Learning Systems and Infrastructure Developer
Siemens
Kitchener, ON
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 23 days 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 23 days ago
S
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 24 days ago
AW
Senior Architecte IA/ML | Senior AI/ML Architect, Services professionnels pour le secteur public | Public Sector Professional Services
Amazon Web Services (AWS)
Montreal, QC
- Full-time
Are you passionate about developing machine learning (ML) and Generative AI (GenAI) solutions? Amazon has been investing in research and application of ML for decades. We are looking for…
Added 24 days ago
Senior Architecte IA/ML | Senior AI/ML Architect, Services professionnels pour le secteur public | Public Sector Professional Services
Amazon
Montreal, QC
Are you passionate about developing machine learning (ML) and Generative AI (GenAI) solutions? Amazon has been investing in research and application of ML for decades. We are looking for…
Added 25 days ago
J
Staff Data Scientist, Applied ML
Jobber
AB · Edmonton, AB
- Full-time
Reporting to the Manager, Data Science, the Staff Data Scientist, Applied Machine Learning will own models and systems for automated decisioning. You will train and evaluate models using…
Added 25 days ago
J
Staff Data Scientist, Applied ML
Jobber
Vancouver, BC
- Full-time
Reporting to the Manager, Data Science, the Staff Data Scientist, Applied Machine Learning will own models and systems for automated decisioning. You will train and evaluate models using…
Added 25 days ago
J
Staff Data Scientist, Applied ML
Jobber
Toronto, ON
- Full-time
Reporting to the Manager, Data Science, the Staff Data Scientist, Applied Machine Learning will own models and systems for automated decisioning. You will train and evaluate models using…
Added 25 days ago
J
Staff Data Scientist, Applied ML
Jobber
Kitchener, ON
- Full-time
Reporting to the Manager, Data Science, the Staff Data Scientist, Applied Machine Learning will own models and systems for automated decisioning. You will train and evaluate models using…
Added 25 days ago
L
Data Scientist
Lantern
AB · Edmonton, AB
- Full-time
Lantern is seeking a hands-on, client-facing Senior Data Scientist to design, develop, and operationalize advanced analytics, machine learning, generative AI, and agentic AI solutions using…

Siemens

Machine Learning Systems and Infrastructure Developer

Kitchener, ON, Canada

Apply About employer

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Job details

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

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

Apply About employer

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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