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Added 7 mins ago
Senior Data Implementation Engineer
Odaia Intelligence Inc.
Toronto, ON
Full-time
As a Senior Data Implementation Engineer reporting to the Manager, Technical Implementations, you will play a critical role in configuring and implementing our AI-driven platform to enable…
Added 23 mins ago
MCP/AI Developer
Autodesk
Toronto, ON · AMER - Canada - Ontario - Toronto - University Ave
Full-time
Debug and troubleshoot across the stack (agent/tool logic, APIs, web UI), collaborating with senior engineers and QA.
Added 52 mins ago
Senior Software Engineer
AgileGrid Solutions
Canada
Full-time
As a Senior Mobile Engineer specializing in iOS at DraftKings, you will play a vital role in shaping the future of our mobile products. Your expertise will help develop and maintain…
Added 52 mins ago
Senior Cloud Platform Engineer (AWS), AI Infrastructure - Evinova
Evinova
Mississauga, ON
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 1 hour ago
Machine Learning Systems and Infrastructure Developer
Siemens
Kitchener, ON
Partner with the Senior AI/ML and Robotics Platform Engineer on dataset readiness, evaluation semantics, and model-quality criteria.
Added 1 hour ago
Senior Data Engineer
TriMech
Oakville, ON
Full-time
As Senior Data Engineer / Data Scientist, you will design, build, and operate the group's data ecosystem: integrating data from our core business systems, developing robust pipelines,…
Added 3 hours ago
Senior Data Engineer
Pomerleau
Montreal, QC
We are building a modern data platform to power our Business Intelligence, AI, and analytics initiatives. As a Senior Data Engineer, you will own the data foundation end to end: ingesting…
Added 4 hours ago
Intermediate Instrumentation and Controls Engineer-Water
Stantec
Burnaby, BC
Full-time
…currently seeking a Intermediate-level Instrumentation and Controls Engineer with strong interest in being part of a purpose-driven organization that is focused on helping our clients,…
Added 5 hours ago
Renewable Energy Engineer (Entry-Level)
Renewable Careers
Toronto, ON
$80,000 to $110,000 CAD / year
Full-time
…are expanding our Toronto team and looking for an entry-level engineer who wants to help build Canada's clean energy…
Added 6 hours ago
Senior Azure Cloud Platform Engineer
Agility IT
Toronto, ON
Contract
Our consulting client is seeking an experienced Senior Azure Cloud Platform Engineer to design, deploy, and support enterprise-grade Azure data and analytics platforms, including Power BI.
Added 7 hours ago
Intern, Developer (Winter 2027)
Bombardier
Mississauga, ON
$17.95 to $31 CAD / hour
Volunteer
Engineer backend automation scripts and data integration pipelines with Python and SQL, leveraging operational data to drive real-time insights and transformation on the shop floor.
Added 8 hours ago
Embedded Software Engineer (C/C++), Machine Learning
Qualcomm
Markham, ON
Full-time
1+ year of work experience in a role requiring interaction with senior leadership (e.g., Director and above).
Added 14 hours ago
Delivery Lead
Fastloop
Vancouver, BC
Full-time
You are a senior, AI-native delivery lead who owns engagement outcomes end to end: shaping the solution, defining and planning the work, leading the client, and making sure what we build is…
Added 14 hours ago
Senior Software Engineer, iOS
Tubi
Toronto, ON
Full-time
As a Senior iOS Engineer at Tubi, you’ll play a critical role on our mobile engineering team, focusing on developing, improving, and maintaining our iOS, tvOS, and visionOS applications.…
Added 14 hours ago
Senior Programmer Analyst (24 Month Contract)
Doctors of BC
Vancouver, BC · BC
Full-time
The Senior Programmer Analyst maintains business continuity for existing applications while progressively migrating business processes, data and functionality to sustainable enterprise…
Added 14 hours ago
Senior Machine Learning Engineer
Takeaway
Edmonton, AB
Full-time
As a Senior ML Engineer you will take a leadership role in shaping the strategic direction of our machine learning infrastructure, proactively identifying opportunities for innovation and…
Added 15 hours ago
Senior Data Engineer
Quandri
Vancouver, BC
Develop and maintain cloud databases with the Infrastructure team, improve data retrieval and optimize analytics dashboards.
Added 15 hours ago
Senior Data Engineer
Quandri
Vancouver, BC · Greater Vancouver Metropolitan Area
Full-time
Develop and maintain cloud databases with the Infrastructure team, improve data retrieval and optimize analytics dashboards.
Added 15 hours ago
Online Calibration & SLAM Engineer
Mecka
Richmond Hill, ON
$200,000 to $230,000 CAD / year
Full-time
We're looking for a hands-on Senior SLAM & Calibration Engineer to own how Mecka's devices stay calibrated after they leave the factory. Cameras and IMUs drift over months and mounts warp,…
Added 16 hours ago
Senior AI Engineer
Workday
Vancouver, BC · Canada, BC, Vancouver
Full-time
As a Senior AI Engineer in Agent Factory, you will drive the end-to-end system design, implementation, and product integration for a core domain of Workday’s next generation of intelligent…
Added 16 hours ago
Software Engineer in Test
Galactic Minds INC
Vancouver, BC
Full-time
Added 16 hours ago
Water Quality Scientist (Junior)
Associated Engineering
Vernon, BC
Full-time
…office. In this role, you will work under the mentorship of senior aquatic scientists, technical specialists, and other experts in their field, and collaborate with colleagues across…
Added 16 hours ago
Software Developer Senior Specialist
Nasdaq
Toronto, ON
Full-time
As a Back-End Software Engineer, Senior Specialist reporting to the Senior Manager you'll play a critical role in designing and delivering cloud-based data solutions that power financial…
Added 16 hours ago
Senior Product Manager - Developer Productivity
Okta
Toronto, ON
We are looking for a Senior Product Manager to own developer productivity as a product across Okta's development lifecycle - AI-native and traditional tooling alike. You will start…
Added 16 hours ago
Senior Software Test Engineer
Coursera
Toronto, ON
As a Senior Software Test Engineer (Test Infrastructure and Tooling) at Coursera, you’ll play a key role in helping teams produce high-quality software for millions of learners across the…

Siemens

Machine Learning Systems and Infrastructure Developer

Kitchener, ON, Canada

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 2, 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.

Siemens is committed to creating a diverse environment and is proud to be an equal opportunity employer. Upon request, Siemens Canada will provide reasonable accommodation for disabilities to support participation of candidates in all aspects of the recruitment process. All qualified applicants will receive consideration for employment.

By submitting personal information to Siemens Canada Limited or its affiliates, service providers and agents, you consent to our collection, use and disclosure of such information for the purposes described in our Privacy Notice available at www.siemens.ca.

Siemens s’engage à créer un environnement diversifié et est fière d’être un employeur souscrivant au principe de l’égalité d’accès à l’emploi. Sur demande, Siemens Canada prendra des mesures d’accommodement raisonnables pour les personnes handicapées, dans le but de soutenir la participation des candidats dans tous les aspects du processus de recrutement. Tous les candidats qualifiés seront pris en considération pour ce poste.

En transmettant des renseignements personnels à Siemens Canada limitée ou à ses sociétés affiliées, à ses fournisseurs de services ou à ses agents, vous nous autorisez à recueillir, à utiliser et à divulguer ces renseignements aux fins prévues dans notre Déclaration de protection de la confidentialité, que vous pouvez consulter au www.siemens.ca.

Job ID

524099

Posted since

01-Oct-2026

Organization

Digital Industries

Field of work

Research & Development

Company

Siemens Canada Limited

Experience level

Experienced Professional

Job type

Full-time

Work mode

Hybrid (Remote/Office)

Employment type

Permanent

Location(s)

Kitchener - Ontario - Canada

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More about this job

Responsibilities

The developer will build and maintain infrastructure for training robotics AI models, including GPU resource management, experiment tracking, and model rollout pipelines. They will collaborate with cross-functional teams to ensure model reproducibility, scalability, and operational readiness.

Requirements

Candidates must hold a Bachelor's or Master's degree in a relevant engineering or science field and possess at least 3 years of experience in ML platform or infrastructure development. Strong proficiency in Python, containerization, and experience with ML frameworks like PyTorch or Ray is required.

Skills

Python
Machine Learning
Robotics
MLOps
Infrastructure Development
Kubernetes
PyTorch
GPU Provisioning
Docker
Slurm
Ray
Model Lifecycle Management
Automation
Linux
CI/CD
Distributed Training

Benefits

Annual discretionary bonus
Flexible work environment
Telecommuting
Digital workspaces
Mentorship programs
Profit sharing
Vacation entitlement
Employee perks and discounts
Social responsibility initiatives

Visa sponsorship

Not detected in the job text

Keywords

Machine Learning
Robotics
Infrastructure
MLOps
Physical AI
Python
Kubernetes
PyTorch
Ray
Slurm
Docker
CUDA
GPU
Model Registry
Automation
CI/CD
VLA
VLM
Perception
Data Lineage
Observability
DevOps
Cloud Infrastructure
On-premise
Distributed Training
Model Lifecycle
Software Engineering
Robotic Foundation Models
Governance
Traceability

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