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Added 13 mins 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 57 mins ago
Infrastructure Automation Engineer
Zodiac Solutions, Inc
Toronto, ON
Full-time
Strong Python skills for automation and tooling
Added 1 hour ago
Satellite Operations Engineer (GEO)
Telesat
Ottawa, ON
Full-time
The Satellite Operations Engineer (GEO) will support all engineering aspects related to ensuring effective in-orbit operations of all on-board subsystems on the assigned GEO satellite bus…
Added 1 hour ago
QA Automation Engineer
SWTCH
Toronto, ON
Full-time
We're looking for a QA Automation Engineer who is passionate about software quality and automation to help ensure our products are reliable, scalable, and deliver an exceptional customer…
Added 1 hour ago
Senior Network Engineer
Kyndryl
Toronto, ON
Contract
Strong assets: Python, Ansible, Terraform or API-based network automation.
Added 1 hour ago
Senior Software Developer in Test (Development Focused)
Royal Bank of Canada
Montreal, QC
Full-time
…matter expert, driving standards, compliance, and strategic automation for development tools and frameworks to enhance architecture and deliver measurable value. You'll blend technical…
Added 1 hour ago
AI Engineer
Stripe
Toronto, ON
Full-time
…users we serve. You'll operate as an embedded, high-context engineer focused on the highest-leverage opportunities across the SA org - building production-quality tooling, supporting our…
Added 1 hour ago
JAMS Platform Engineer
J&M Group
Toronto, ON
Contract
10+ years of total IT experience required; hands-on expertise in JAMS Scheduler/workload automation and enterprise platform engineering.
Added 1 hour ago
Quality Engineer
BayOne Solutions
Canada
Contract
The client is looking for a QE Engineer who is strong in test automation, Playwright, and AI/agentic testing, with retail industry experience. The role is focused more on hands-on execution…
Added 2 hours ago
3D Software engineer
SQUALUS GROUP
ON · Richmond Hill Central, Ontario
Full-time
robotics and automation software. The candidate should have strong engineering
Added 2 hours ago
JAMS Platform Engineer
Pacer Group
Toronto, ON
$65 to $70 CAD / hour
Contract
Strong hands-on experience with JAMS Scheduler and workload automation
Added 3 hours ago
Layout Design, Engineer
Synopsys
Ottawa, ON
Automation does not intimidate you. Whether it is Python, PCL, or something else, you see scripting as a tool to make repetitive work faster and more accurate. You want to learn, you want…
Added 3 hours ago
Principal Firmware Engineer
Synopsys
Ottawa, ON
Experience with Python and Verilog is a strong plus, particularly for test automation and RTL co-development
Added 3 hours ago
Principal Physical Design Methodology Engineer
Synopsys
Markham, ON
Solid scripting skills in Tcl and Python for flow automation, analysis, and reporting
Added 3 hours ago
Principal SI/PI Engineer - 18619
Synopsys
Mississauga, ON
You are a highly skilled and passionate engineer with a deep understanding of high-speed signal and power integrity, particularly in the realm of SerDes interfaces. With a proven track…
Added 3 hours ago
Systems Software Engineer - EA SPORTS™ NHL
Electronic Arts
Vancouver, BC
We're looking for a Systems Software Engineer or someone interested in expanding their knowledge in the Systems area. Our Systems Engineers maintain a broad view of the game and engine…
Added 3 hours ago
Systems Software Engineer - EA SPORTS™ NHL
Electronic Arts
Vancouver, BC
We're looking for a Systems Software Engineer or someone interested in expanding their knowledge in the Systems area. Our Systems Engineers maintain a broad view of the game and engine…
Added 3 hours ago
Senior Verification Manager, SERDES PHY
Synopsys
Mississauga, ON
Define and evolve UVM and mixed-signal co-simulation methodology, regression standards, reuse strategy, and automation frameworks using Shell, Perl, Python, and C++
Added 3 hours ago
Silicon Validation Engineer
Synopsys
Mississauga, ON
Proficiency in MATLAB and Python for test automation, data analysis, and post-processing of measurement results
Added 3 hours ago
Silicon Validation Software Engineer (Sr Staff)
Synopsys
Mississauga, ON
Design, develop, and maintain Python-based automation frameworks and software tools that drive silicon validation, characterization, and system-level debug workflows
Added 3 hours ago
Silicon Validation/Characterization Engineer - 18757
Synopsys
Ottawa, ON
Experience with scripting any programming languages such as MATLAB/ Python/ Visual Basic/ TCL/ PERL as well C/C++ & test automation
Added 3 hours ago
Machine Learning Systems and Infrastructure Developer
Siemens
Kitchener, ON
Full-time
Strong programming skills in Python and practical experience with containers, Linux, automation, APIs, configuration management, and reproducible environments.
Added 3 hours ago
Presentation Software Engineer - EA SPORTS™ NHL (TFT)
Electronic Arts
Vancouver, BC
Experience with scripting or managed languages (e.g., Python, C#, Lua) for tooling and automation is a plus.
Added 3 hours ago
St Staff R&D Engineer
Synopsys
Waterloo, ON
Solid experience with Python for scripting, automation, and backend services
Added 3 hours ago
Staff R&D Engineer-17397
Synopsys
Vancouver, BC
Build high-performance C++ software and Python-based automation tools

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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