Jobs in Canada

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Added 1 month ago
OM
Analyst, Service Desk
Ontario Medical Association
Toronto, ON
- Full-time
Preference will be given to candidates with experience in CompTIA Security+ (or equivalent security awareness); Windows 11, macOS, iOS/Android device management; Microsoft 365…
Added 1 month ago
OM
Analyst, Service Desk
Ontario Medical Association
Toronto, ON
- Full-time
Preference will be given to candidates with experience in CompTIA Security+ (or equivalent security awareness); Windows 11, macOS, iOS/Android device management; Microsoft 365…
Added 1 month ago
S
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 1 month ago
T
Satellite Operations Engineer (GEO)
Telesat
Ottawa, ON
- Full-time
…combination of high capacity, security, resiliency and affordability with ultra-low latency and fiber-like speeds. Telesat is headquartered in Ottawa, Canada, and has offices and facilities…
Added 1 month ago
B
Software Engineer I
Beanfield
Toronto, ON
- $90,000 to $110,000 CAD / year
- Full-time
…enhancing backend systems, APIs, and data processing tools using Python, Java and modern web frameworks. The Software Engineer will collaborate with product managers and other team members…
Added 1 month ago
A
Databricks Manager
Avanade
Toronto, ON
- Full-time
…you're passionate about helping clients transform their business with the latest AI and data technologies, let's talk. Take your skills to a new level and launch a career where you can…
Added 1 month ago
F
Data Scientist, Risk Modeling & Analytics
Financeit
Remote, Canada
- Full-time
- Remote
Foundational experience with Python, SQL, Excel, or similar analytical tools; experience building models, working with data, or automating processes is a strong asset
Added 1 month ago
O
Principal Machine Learning Engineer, SecureAI
Okta
Toronto, ON
- $192,000 to $264,000 CAD / year
- Full-time
10+ years of software development experience, with strong programming expertise in Python (and familiarity with Go or Typescript a plus).
Added 1 month ago
F
Data Scientist, Risk Modeling & Analytics
Financeit
Toronto, ON
- $75,000 to $100,000 CAD / year
- Full-time
Foundational experience with Python, SQL, Excel, or similar analytical tools; experience building models, working with data, or automating processes is a strong asset
Added 1 month ago
Software Engineering Intern 2027 (Toronto)
Pinterest
Toronto, ON
This onsite internship will be based in our Toronto office requiring a few days in office
Added 1 month ago
Machine Learning Intern 2027 (Toronto)
Pinterest
Toronto, ON
This onsite internship will be based in our Toronto office requiring a few days in office
Added 1 month 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 1 month ago
Principal Physical Design Methodology Engineer
Synopsys
Markham, ON
You think in tradeoffs. PPA is not a buzzword to you, it is the conversation you have every day with designers who want faster clocks, lower power, and smaller area, and you are the one who…
Added 1 month ago
UI / Frontend Technical Artist - EA Sports NHL
Electronic Arts
Vancouver, BC
…around the world through play. If you're a creative pioneer with a passion for your craft, this will be more than a job. It’ll be what you…
Added 1 month ago
Technical Artist - EA SPORTS™ UFC
Electronic Arts
Vancouver, BC
…optimization across multiple platforms. You’ll collaborate closely with our rendering engineers and art leads to build, test, refine and debug anything that comes between that perfect blend…
Added 1 month ago
Systems Software Engineer - EA SPORTS™ NHL
Electronic Arts
Vancouver, BC
Experience with multiple programming languages (Python, Lua, C#).
Added 1 month ago
Systems Software Engineer - EA SPORTS™ NHL
Electronic Arts
Vancouver, BC
Experience with multiple programming languages (Python, Lua, C#).
Added 1 month ago
Silicon Validation Software Engineer (Sr Staff)
Synopsys
Mississauga, ON
You are comfortable sitting with an analog designer reviewing scope traces one hour and writing Python to parse gigabytes of characterization data the next. You do not wait for perfect…
Added 1 month ago
Silicon Validation/Characterization Engineer - 18757
Synopsys
Ottawa, ON
You are comfortable in the lab with an oscilloscope in one hand and a Python script in the other, moving between electrical measurements and data analysis without losing sight of what you…
Added 1 month ago
C
Data Engineer – PySpark & SQL
Capgemini
Mississauga, ON
- Full-time
Candidate must hold at least one relevant, active Data Engineering or Cloud certification, preferably from:
Added 1 month ago
S
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 1 month 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 1 month ago
Sr. Staff AI Full Stack Engineer
Synopsys
Canada Off-Site, Canada Off-Site Office
…of software engineering principles and a strong command of Python, with the ability to architect, build, and maintain distributed systems and AI/ML solutions. Your experience spans backend…
Added 1 month ago
St Staff R&D Engineer
Synopsys
Waterloo, ON
Solid experience with Python for scripting, automation, and backend services
Added 1 month ago
Machine Learning Engineer - EA SPORTS™ FC
Electronic Arts
Vancouver, BC
As one of the largest sports entertainment platforms in the world, EA SPORTS™ FC is redefining football with genre-leading interactive experiences, connecting a global community of fans to…

Siemens

Machine Learning Systems and Infrastructure Developer

Kitchener, ON, Canada

Full-time

Apply on LinkedIn About employer

Applications open in a new tab.

Job details

Job type: Full-time
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

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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Work requirements

Jobs in Canada