Find work in Canada.

322,693 jobs across our Canadian network. How we count

Jobs in Canada

25+ jobs

Email me new jobs Save this search

Added 4 mins ago
Software Engineer I
Beanfield
Toronto, ON
$90,000 to $110,000 CAD / year
Full-time
We are seeking a motivated Software Engineer to join our technology team. This role focuses on designing, developing, and enhancing backend systems, APIs, and data processing tools using…
Added 4 mins ago
Senior Analytics Engineer – Data Modeling
SPECTRAFORCE
Toronto, ON · Greater Toronto Area, Canada
Contract
Senior Analytics Engineer – Data Modeling (Databricks), Capital Markets
Added 5 mins ago
Lead, Software Engineer (Implementations)
Broadridge
Toronto, ON
Full-time
Coordinate deployment of application components and data into test environments
Added 5 mins ago
Lead, Software Engineer
Broadridge
Toronto, ON
Full-time
We are looking for an experienced, adaptable Software Engineer to join the Securities Finance and Collateral Management (SFCM) engineering team at Broadridge. In this hands-on role, you…
Added 5 mins ago
Intern, AI Data Developer (Winter)
Autodesk
Toronto, ON · AMER - Canada - Ontario - Toronto - University Ave
Full-time
As an AI Data Developer Intern on the Advanced Compliance Products (ACP) team at Autodesk, you will help build and scale the data pipelines, models, and platform integrations that power…
Added 5 mins 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 21 mins ago
Senior Front End Engineer
Spare
Remote, Canada
$151,000 to $208,000 CAD / year
Full-time · Remote
As a Senior Frontend Engineer, you’d turn the Design team’s direction into the product people actually use. You’d own the technical calls that keep our interfaces accessible, fast, and…
Added 21 mins 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 21 mins ago
Platform/DevOps Engineer
Vasco
Remote, Canada
Full-time · Remote
…all the time. We structure CRM, billing, calls, and support data into a semantic layer where every metric is sourced, every definition is locked, and every answer is deterministic, then…
Added 21 mins ago
Power Engineer - Second Class
''
Grand Falls, NB
From $45.32 CAD / hour
Full-time · Temporary
Position Title: Power Engineer - Second Class
Added 21 mins ago
Senior Software Developer in Test (Development Focused)
Royal Bank of Canada
Montreal, QC
Full-time
…execution, reduce manual effort, and implement intelligent test data generation with anomaly detection…
Added 35 mins 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 35 mins ago
JAMS Platform Engineer
J&M Group
Toronto, ON
Contract
Administer and engineer JAMS Scheduler, Agents, Executors, queues, resources, and job configurations, focusing on reliability, performance, capacity, resilience, and observability.
Added 35 mins ago
Principal Machine Learning Engineer, SecureAI
Okta
Toronto, ON
$192,000 to $264,000 CAD / year
Full-time
…under Okta Secures AI as a Principal Machine Learning (ML) Engineer to advance Okta's authorization capabilities. By replacing static, rule-based systems with dynamic AI security…
Added 35 mins ago
Sr. GCP/ Java Developer
NTT DATA North America
Toronto, ON
Other
NTT DATA strives to hire exceptional, innovative and passionate individuals who want to grow with us. If you want to be part of an inclusive, adaptable, and forward-thinking organization,…
Added 1 hour ago
08 - Lead Engineer, Systems/Applications Design
Celestica International LP
Newmarket, ON
…deliver high quality solutions in a Tool room environment. The Engineer, Systems/Applications designs, integrates, and produces robust tooling solutions and manages systems over their life…
Added 1 hour ago
University Grad Software Engineer (Toronto)
Pinterest
Toronto, ON
…our engineering teams. Working closely with product, design, data, and back‑end engineers, you’ll learn how large‑scale systems operate and play a meaningful role in building new…
Added 1 hour ago
University Grad Machine Learning Engineer 2027 (Toronto)
Pinterest
Toronto, ON
As a Machine Learning Engineer at Pinterest, you’ll develop and improve machine learning systems that power product experiences and discovery. You’ll partner with engineering, product and…
Added 1 hour ago
Senior Full Stack Developer
Capgemini
Mississauga, ON
7 years experience as a successful full stack software engineer, delivering software using agile development practices.
Added 1 hour ago
Staff Data Infrastructure Engineer
Faire
Toronto, ON · Kitchener, ON
We are hiring a Staff Engineer to own that plumbing. Concretely, this means the path data takes out of our production databases (CockroachDB and MySQL) and into a place where analysts and…
Added 1 hour ago
Analog Design, Sr Staff Engineer - 17402
Synopsys
Mississauga, ON
Support electrical characterization, analyze customer silicon data, and contribute to post-silicon improvements.
Added 1 hour ago
ATE Test Engineer, Sr Staff Engineer - 18756
Synopsys
Ottawa, ON
Your characterization data will inform design decisions for next-generation memory interface IP
Added 1 hour ago
Hardware Validation Engineer, Sr Staff
Synopsys
Ottawa, ON
Your board designs will serve as the validation platform for Synopsys memory IP used in customer production deployments across automotive, mobile, and data center applications
Added 1 hour ago
Principal Firmware Engineer
Synopsys
Ottawa, ON
Analyze RTL waveforms and testchip data in the hardware lab to understand eye margin sensitivity and refine training algorithms
Added 1 hour ago
R&D Engineering , Sr Engineer
Synopsys
Vancouver, BC
…problems. You look at a 3D surface or a volume mesh and see the data structures, the edge cases, the numerical precision traps that will bite someone six months from now if you do not catch…

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

Apply About employer

Applications open in a new tab.

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

Apply About employer

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

Report this job