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Added 15 mins ago
Senior Cloud Platform Engineer (AWS), AI Infrastructure - Evinova
AstraZeneca
Mississauga, ON · Canada - Mississauga
Full-time
As a Senior Cloud Platform Engineer on the ML/AI Ops team, you will design, build and operate the AWS platform that runs our production Generative AI, agentic AI and conversational AI…
Added 43 mins ago
AI Platform Engineer - DevOps, Python
Astra-North Infoteck Inc. ~ Conquering today’s challenges, achieving tomorrow’s vision!
Halifax, NS
Full-time
AI Platform Engineer - DevOps | Python, TypeScript, CI/CD, Kubernetes, LLMOps
Added 43 mins ago
Lead Architect / Principal Engineer
Litmus
Toronto, ON
Full-time
15+ years of software engineering experience, with a clear track record of org-wide architectural impact.
Added 43 mins ago
AI Platform Engineer - DevOps
J&M Group
Halifax, NS
Full-time
Enterprise AI/GenAI, LLM, LLMOps/MLOps platform experience
Added 1 hour ago
Database Engineer
THE CANADIAN REAL ESTATE ASSOCIATION
Ottawa, ON
$110,000 to $135,000 CAD / year
Full-time
We are seeking an experienced Database Engineer to join our Database Engineering team and help support its evolving responsibilities. This role combines database engineering, database…
Added 1 hour ago
Development Lead - Air Canada Mobile Application
Air Canada
Toronto, ON
…engineering standards and technical debt strategy for the mobile platform) with delivery leadership (code quality, release readiness and production stability) across the mobile delivery…
Added 1 hour ago
Sr Full Stack AI Engineer - Calgary ,Canada (Hybrid)
Straive
Calgary, AB
Full-time
We are seeking a Senior Full Stack AI Engineer who can combine strong hands-on software engineering with technical engagement and project delivery leadership. The successful candidate will…
Added 2 hours ago
Senior Solutions Engineer, Enterprise Technology Services
Manulife
Toronto, ON
Full-time
In this role, you’ll provide technical leadership across Azure platform architecture, CI/CD strategy, and infrastructure as code. You’ll partner closely with engineering teams and…
Added 2 hours ago
Software Engineer (Product - Backend)
Vasco
Remote, Canada
Full-time · Remote
As a Software Engineer at Vasco, you'll build the brain of our agents: the core systems that give them the context, metrics, and playbooks they need to do their job. You'll join a small…
Added 2 hours ago
Platform/DevOps Engineer
Vasco
Remote, Canada
Full-time · Remote
Platform/DevOps at Vasco has been a shared responsibility across our engineers. We're now hiring the first owner of our DevOps practice and infrastructure platform. In this role, you'll be…
Added 2 hours ago
AI Engineer
Stripe
Toronto, ON
Full-time
As an AI Engineer, you'll be embedded directly with the Solutions Architecture team - building alongside them, deeply understanding their workflows, and shipping tools and automation that…
Added 2 hours ago
Sr. GCP/ Java Developer
NTT DATA North America
Toronto, ON
Other
3+ years of experience collaborating with DevOps and SRE teams to improve deployment reliability and operational efficiency.
Added 4 hours ago
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 4 hours ago
Senior DevOps Engineer - PA145
ZoomInfo Technologies LLC
Toronto, ON
Drive adoption of company standards and influence data teams to align with best DevOps and SRE practices.
Added 4 hours ago
Senior DevOps Engineer - PA145
ZoomInfo
Toronto, ON
Full-time
Drive adoption of company standards and influence data teams to align with best DevOps and SRE practices.
Added 4 hours ago
AI Platform Engineer
LanceSoft, Inc.
Halifax, NS
$55 to $60 CAD / hour
Contract
AI Platform EngineerDevOps - Halifax Job DescriptionWhat is the Opportunity?Are you looking to make an impact across many teams? Excited at the thought of transforming the flows that help…
Added 5 hours ago
System Engineer
TEEMA
Vancouver, BC
$60,000 to $70,000 CAD / year
Full-time
Seeking a Junior Systems Engineer to join a Backend & Platform Engineering team in Vancouver. This is a great opportunity for someone early in their career who is interested in cloud…
Added 5 hours ago
Azure Data Engineer (Automation & Integration)
Global X Canada
Toronto, ON
$85,000 to $100,000 CAD / year
Full-time
Support the Senior Azure Data Engineer across the data platform, taking on development, maintenance and operational tasks, and serving as backup coverage when they are unavailable.
Added 5 hours ago
AI Engineer
AgileGrid Solutions
Canada
Full-time
We are seeking a highly skilled Platform Operations Specialist to join our dynamic technology team. In this role, you will be responsible for supporting and maintaining our customer-facing…
Added 6 hours ago
Cloud Security Engineer
Paymentus Group Inc
Richmond Hill, ON
Full-time
The Cloud Security Engineer is responsible for helping secure the cloud-native infrastructure, platforms, services, and deployment patterns that support the Paymentus SaaS platform. This…
Added 6 hours ago
Senior AI Platform Security Engineer
Charger Logistics Inc.
Brampton, ON
Full-time
5+ years in cloud platform, DevOps/SRE or cloud security engineering, with strong GCP depth. A Professional Cloud Security Engineer or Professional Cloud Architect certification is a plus.
Added 7 hours ago
Senior AI Platform Security Engineer
Charger Logistics Inc
Brampton, ON
5+ years in cloud platform, DevOps/SRE or cloud security engineering, with strong GCP depth. A Professional Cloud Security Engineer or Professional Cloud Architect certification is a plus.
Added 9 hours ago
←
Quartz
Open Hall, NL
Full-time
Quartz is reimagining wealth management through personalised intelligence. It's the first wealth platform that truly learns from you, understands your goals, and helps you make confident,…
Added 18 hours ago
QA Automation Engineering Consultant
CGI
Toronto, ON
Full-time
We are seeking an experienced QA Automation Engineer to support enterprise branch-banking applications deployed across on-premises and Google Cloud Platform (GCP) environments. The…
Added 20 hours ago
Senior Cloud Security Engineer ( Global Security)
Royal Bank of Canada
Toronto, ON · Vancouver, BC
Full-time
5+ years of cloud engineering experience with demonstrated experience in developing AWS cloud security solutions.

Siemens

Machine Learning Systems and Infrastructure Developer

Kitchener, ON, Canada

Job type: Full-time
Apply by: Oct 31, 2026
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

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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.

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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