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Added 29 mins ago
Principal Front-Office Trading Integration Engineer - Vice President - Java, Talend, Kafka, ETL - Charles River Development -
State Street
Toronto, ON
Full-time
Principal Front-Office Trading Integration Engineer / Principal Consultants you will be assessing client needs and utilizing technical expertise to identify solutions which are in alignment…
Added 29 mins ago
Bid Lead, Engineering and Field Services
AtkinsRéalis
Mississauga, ON
Full-time
…while assembling a proposal team with the relevant service, product and business knowledge required to…
Added 43 mins ago
Director, Mechanical Engineering
Photonic Inc.
Coquitlam, BC
$193,300 to $265,800 CAD / year
Full-time
Lead the team to engineer complex assemblies, in collaboration with external development and manufacturing partners.
Added 44 mins ago
Software Engineer II (Fullstack), Growth Platform
Scribd, Inc.
Toronto, ON · Vancouver, BC
Full-time
We are seeking a determined Fullstack Software Engineer to join our Growth Platform team. In this role, you will design, build, and scale the shared systems that power Growth at Scribd,…
Added 59 mins ago
Staff Quantum Engineer (Qubit System Performance)
Photonic Inc.
Coquitlam, BC
$161,000 to $222,600 CAD / year
Full-time
As Staff Quantum Engineer – Performance at Photonic, you are a leader on the spin-photon qubit development team where you will play a crucial role in enhancing the performance of qubit…
Added 1 hour ago
Delivery Lead
Fastloop
Vancouver, BC
Full-time
You partner with a Technical Lead / AI-Forward Engineer, working as one team: you bring the problem, the outcome, the sequencing, and the adoption; the TL brings the architecture and the…
Added 1 hour ago
Bid Lead, Engineering and Field Services
AtkinsRéalis
Mississauga, ON
Full-time
…while assembling a proposal team with the relevant service, product and business knowledge required to…
Added 1 hour 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 1 hour ago
Bid Lead, Engineering and Field Services
AtkinsRéalis
Mississauga, ON
Full-time
…while assembling a proposal team with the relevant service, product and business knowledge required to…
Added 1 hour ago
Manager, Design Engineering
Sentry
Toronto, ON · Greater Toronto Area, Canada
Full-time
Drive adoption across product teams through documentation, lint rules, and contribution workflows that don't slow anyone down
Added 2 hours ago
Senior Data Engineer
Quandri
Vancouver, BC
…serviced. Yet operating an agency is harder than ever. Peak product complexity, accelerating consolidation, a deepening talent crisis, and the AI revolution are all reshaping how agencies…
Added 2 hours ago
Senior Data Engineer
Quandri
Vancouver, BC · Greater Vancouver Metropolitan Area
Full-time
…serviced. Yet operating an agency is harder than ever. Peak product complexity, accelerating consolidation, a deepening talent crisis, and the AI revolution are all reshaping how agencies…
Added 3 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 3 hours ago
Principal Software Engineer - Evisort AI
Workday
Vancouver, BC · Canada, BC, Vancouver
Full-time
Evisort Engineering is growing! As a Principal Software Engineer, you’ll join a collaborative, cross-functional team working to enhance and expand our AI-driven contract management…
Added 3 hours ago
Principal Front-Office Trading Integration Engineer - Vice President - Java, Talend, Kafka, ETL - Charles River Development -
Charles River Development
Toronto, ON
Full-time
Principal Front-Office Trading Integration Engineer / Principal Consultants you will be assessing client needs and utilizing technical expertise to identify solutions which are in alignment…
Added 3 hours ago
Adobe DAM Lead Engineer
J&M Group
Canada
Full-time
The Adobe DAM Lead Engineer (Onsite) serves as the primary client-facing technical lead responsible for managing Adobe Experience Manager (AEM) Assets/DAM support and enhancement services.…
Added 3 hours ago
Director of Customer Success
Magna Search Group
Canada
Full-time
Internally, you will act as the customer's quarterback, working cross-functionally with Product, Engineering, Field Engineering, Delivery, Support, Sales, and Account Management.
Added 3 hours ago
Aircraft Maintenance Engineer Third Party
Babcock Canada Inc.
Winnipeg, MB
Full-time
Babcock is an international defence company providing support and product solutions to enhance our customers’ defence capabilities and critical assets.
Added 3 hours ago
Designer, Development (Service)
Husky Technologies
Bolton, ON
Full-time
…resolving systemic service issues. The team is responsible for all product lines (Machines, Molds, 3rd Party Hot runners, Controllers, and Auxiliaries) and works cohesively with a variety…
Added 3 hours ago
Product Development Engineer|
Husky Technologies
Bolton, ON
Full-time
Our Development Engineering team is looking to hire an experienced Product Development Engineer. The successful candidate will lead the technical development of packaging products working…
Added 3 hours ago
Manufacturing Engineer (Contract)
Husky Technologies
Bolton, ON
Full-time
We have an opening for an Industrial / Manufacturing Engineer working with our Manufacturing Engineering Team as outlined below:
Added 3 hours ago
Applications Engineer
Husky Technologies
Bolton, ON
Full-time
Analyze global rigid packaging, beverage, and consumer goods trends to shape application strategies, product roadmaps, and innovation priorities.
Added 3 hours ago
Software Developer (iOS)
Priceline
Toronto, ON
Full-time
Collaborate with passionate developers, product, and UI/UX specialists to create fast, stable native solutions built on top of Apple's latest iOS sdk.
Added 3 hours ago
Electronics Engineering Contractor
MistyWest
Remote, Canada
Full-time · Remote
At MistyWest, as our Electronics Engineer, you will work on various electronic designs and cover all stages of the design process from specifications and high-level design, to testing and…
Added 3 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…

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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