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Added 10 mins ago
OT Senior Systems Engineer
CBRE
Toronto, ON
Full-time
As a CBRE OT Senior Systems Engineer, you will manage infrastructure resources by monitoring system platforms and information technology operations. This job is part of the System…
Added 56 mins ago
Ingénieur régional en colo électrique Sénior (Elec Colo Regional Engineer), Colocation Region Engineering- AMER
Amazon
Pointe-Claire, QC
Are you an engineer with a passion for data center design and looking for a challenge to chart your own course? If so, we are looking for you to help us make history.
Added 1 hour ago
Development Lead - Air Canada Mobile Application
Air Canada
Toronto, ON
As the most senior engineer on the mobile application, the Development Lead is both the design authority for the mobile platform and the primary delivery authority within Air Canada’s…
Added 2 hours ago
Senior Solutions Engineer, Enterprise Technology Services
Manulife
Toronto, ON
Full-time
Manulife is seeking a Senior Solutions Engineer to help design, scale, and modernize secure cloud platforms that support critical business systems across a global financial services…
Added 3 hours ago
Cloud & Application Security Engineer
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Quebec, QC
Full-time
As the Cloud & Application Security Engineer, you will serve as the principal design authority responsible for protecting our enterprise applications and hybrid multi-cloud digital…
Added 3 hours ago
Senior Full Stack Engineer
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Toronto, ON
The team is searching for a client-focused full stack engineer who is motivated to design and develop components of enterprise applications and providing consultative guidance on all…
Added 3 hours ago
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 3 hours ago
Senior Security Analyst (Bilingual French/English)
TEKsystems
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$70 to $80 CAD / hour
Contract
-5+ years of experience in a Security Analyst, Security Engineer, or similar cybersecurity role.
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
AI Engineer Intern
Electronic Arts
Vancouver, BC
The Infrastructure and Platform Services (IPS) team serves as the backbone of EA's global ecosystem, supporting the creation of exceptional games and immersive player experiences. We offer…
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Machine Learning Engineer III
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Vancouver, BC
The Senior Machine Learning Engineer will report to the Senior Manager, EA Player Security Data Labs. You will follow a hybrid work model with a mix of remote work and in-office…
Added 4 hours ago
Développeur.se de logiciels sénior.e - applications dorsales / Senior Software Developer - Backend
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Montreal, QC · Vancouver, BC
As a Senior Software Engineer, you will collaborate with Research Scientists and Engineers to shape how new technologies integrate into backend architecture. You will translate ideas from…
Added 4 hours ago
Développeur.se sénior.e des données d’apprentissage automatique / Senior ML Data Developer
Electronic Arts
Montreal, QC · Vancouver, BC
As a Senior ML Data Engineer, you will own the layer between raw game capture and research-ready datasets. You will define how multimodal game data is structured, enriched, evaluated,…
Added 4 hours ago
Senior Systems Engineer - Identity and Access Management
Electronic Arts
Vancouver, BC
We are looking for an experienced Senior Systems Engineer with deep expertise in both Identity & Access Management (IAM) and Windows Systems Administration to join our Identity Security…
Added 6 hours ago
Azure Data Engineer (Automation & Integration)
Global X Canada
Toronto, ON
$85,000 to $100,000 CAD / year
Full-time
Global X Investments Canada Inc. is seeking an Azure Data Engineer to help build, support and automate our Azure-based data infrastructure. Reporting to the SVP, Digital Innovation & Data…
Added 6 hours ago
Senior Sales Engineer - Data Protection
N-able
ON
Full-time
…confidence. But the real power behind it all? Our people. We’re a global crew of N-ablites, who love solving complex problems, sharing knowledge, and delivering solutions that actually make…
Added 7 hours ago
Lead Senior Developer
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Quebec, QC · Greater Quebec City Metropolitan Area
Full-time
This role requires strong hands-on expertise in React-based frontend development, cloud-native solutions on Microsoft Azure, and CI/CD practices using Azure DevOps. As Lead Senior…
Added 11 hours ago
Cloud Platform - Senior Engineer
Emplo Inc.
Ottawa, ON
Full-time
Wind River is a global leader in delivering software for mission-critical intelligent systems. For more than four decades, the company has been an innovator and pioneer, powering billions…
Added 19 hours ago
Principal Data Quality and Governance Engineer
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Full-time
Working closely with business data governance stakeholders, data engineering, architecture, analytics, and security teams, the Principal Data Quality and Governance Engineer enables…
Added 20 hours ago
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
AWS Global Sales favorise l'adoption du cloud AWS à l'échelle mondiale, permettant aux clients de toutes tailles d'innover et de se développer dans le cloud. Notre équipe permet à chaque…
Added 20 hours ago
Ingénieur principal en plateforme (SRE), solutions d'IA/Senior Platform Engineer (SRE), AI Solutions
Syntax
Montreal, QC
Syntax is a leading Managed Cloud Provider for Mission Critical Enterprise Applications and has been providing comprehensive technology solutions to businesses of all sizes since 1972.…
Added 20 hours ago
Senior Cloud Security Engineer ( Global Security)
Royal Bank of Canada
Toronto, ON · Vancouver, BC
Full-time
The AWS Security Controls team within Cloud Security Engineering is working on several exciting initiatives to further secure RBC’s AWS environment. In this role as a Senior Cloud Security…
Added 23 hours ago
Senior SailPoint IIQ Engineer
Cognizant
Brampton, ON
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Practice - CIS - Cloud, Infrastructure, and Security Services
Added 23 hours ago
Senior Java Microservices Engineer
Publicis Sapient
Calgary, AB
Full-time
We are looking for highly skilled Senior Java Microservices Engineer to join a strategic client engagement in Calgary. We are looking for a hands-on senior engineer who combines strong…
Added 23 hours ago
Senior Software Engineer, Security Engineering (Auth0)
Okta
Toronto, ON
Senior Software Engineer, Security Engineering

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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