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Robotics Engineer, Teleoperation and Data Collection - Physical AI Hub, Kitchener

  • Kitchener, ON, Canada

Full-time

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Job details

Job type
Full-time
Apply by
Experience
3+ years experience building data pipelines, data platforms, telemetry systems, ML data infrastructure, or high-volume event-based storage.
Posting language
English
Posted

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 passionate about turning real robot operation into high-quality data? Do you enjoy designing data systems that capture synchronized robot state, sensor streams, task events, teleoperation input, and outcome evidence with enough fidelity to support evaluation and improvement?

We are seeking a Robotics Data Engineer to build the teleoperation and data collection layer for the Physical AI Runtime. This engineer will design pipelines for demonstration data, event-based storage, compression, curation, labeling, data quality, and reusable evaluation corpora. The role is central to building a data flywheel for robot skills, perception monitoring, VLA evaluation, and runtime validation.

What you will do:

  • Build data pipelines for teleoperation sessions, robot state, camera streams, sensor data, task events, and runtime traces.
  • Define schemas and storage patterns for synchronized multimodal robotics episodes.
  • Implement event-based capture, buffering, compression, upload, validation, indexing, and replay workflows.
  • Support curation, labeling, review, dataset versioning, access control, and quality reporting.
  • Create data-quality checks for timing drift, dropped frames, missing metadata, incomplete episodes, and corrupted artifacts.
  • Partner with Perception, ML Systems, QA, and Robotics Integration engineers on evaluation corpora and failure analysis.
  • Help define governance for demonstration recordings, operator data, customer data separation, and retention expectations.

What you will bring:

  • Bachelor's or Master's degree in Computer Science, Data Engineering, Robotics, Electrical Engineering, Software Engineering, Computer Engineering, or a related field.
  • 3+ years experience building data pipelines, data platforms, telemetry systems, ML data infrastructure, or high-volume event-based storage.
  • Strong programming skills in Python and practical experience with SQL, object storage, data formats, schema design, APIs, or streaming systems.
  • Experience handling time-synchronized, multimodal, or high-frequency data such as video, images, robot state, sensor signals, traces, logs, and task events.
  • Understanding of data lineage, dataset versioning, retention, compression, privacy, access control, and reproducible data processing.
  • Ability to define data-quality checks for missing frames, dropped events, clock drift, inconsistent metadata, corrupted files, and incomplete episodes.
  • Experience supporting labeling, curation, review workflows, and dataset discoverability by task, skill, outcome, failure mode, or environment.
  • Ability to collaborate with robotics integration, perception, ML systems, QA, and product teams on shared data contracts.
  • Practical judgment about balancing capture fidelity, storage cost, network constraints, and operational simplicity.

What sets you apart:

  • Experience with robotics data, teleoperation, imitation learning, robot-learning datasets, reinforcement learning data, or demonstration capture.
  • Experience with video pipelines, image sequences, point clouds, time-series databases, event streams, ROS bags, MCAP, Parquet, HDF5, or similar data formats.
  • Knowledge of teleoperation systems, human demonstration workflows, operator input capture, annotation tools, or human-in-the-loop review.
  • Experience building data products for model evaluation, failure analysis, replay, simulation, or regression testing.
  • Familiarity with edge capture, offline-first upload, compression strategies, bandwidth constraints, and local buffering.
  • Ability to reason about what makes a robotics episode useful for training, evaluation, debugging, and customer evidence.
  • Strong ownership of data quality as an engineering and product requirement.

Work environment:

  • This role includes hands-on collaboration with teleoperation setups, robot-cell data capture, camera streams, edge devices, and lab validation workflows.
  • Hybrid work is supported, with on-site presence expected for teleoperation data collection, synchronization debugging, and reference-cell validation

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.

Salary is commensurate with experience, and ranges between $ X CAD - $ X CAD, excluding bonus and benefits. In addition to base salary, this role includes eligibility for an annual discretionary bonus of 10% base salary, based on Company performance metrics. 

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

More about this job

Responsibilities

Build and maintain pipelines and storage workflows for synchronized teleoperation sessions, robot state, camera and sensor streams, task events, and runtime traces. Establish data quality, curation, labeling, versioning, replay, and governance practices, and collaborate with robotics, perception, ML systems, and QA teams on evaluation datasets and failure analysis.

Requirements

A bachelor's or master's degree in a relevant computing, engineering, or robotics field and at least three years of experience building data pipelines, data platforms, telemetry systems, ML data infrastructure, or event-based storage are requested. Candidates should have strong Python skills, practical experience with SQL and data systems, familiarity with synchronized multimodal data and data-quality practices, and the ability to collaborate across engineering teams.

Skills

  • Python
  • SQL
  • Data Pipeline Engineering
  • Robotics Data Collection
  • Teleoperation
  • Multimodal Data Synchronization
  • Data Schema Design
  • Event-Based Storage
  • Data Compression
  • Data Quality Validation
  • Dataset Versioning
  • Data Curation and Labeling
  • Data Lineage
  • Streaming Systems
  • Video Processing
  • Cross-Functional Collaboration

Benefits

  • Flexible Work Environment
  • Flexible Hours
  • Telecommuting
  • Career Advancement Opportunities
  • Mentorship Programs
  • Profit Sharing
  • Vacation Entitlement
  • Employee Perks and Discounts

Visa sponsorship

Not detected in the job text

Categories

  • Engineering
  • Technology
  • Data & Analytics
  • Software
  • Manufacturing

Keywords

  • Python
  • SQL
  • Teleoperation
  • Physical AI
  • Robotics Data
  • Data Pipelines
  • Robot State
  • Camera Streams
  • Sensor Data
  • Runtime Traces
  • Multimodal Data
  • Event-Based Storage
  • Data Compression
  • Data Curation
  • Data Labeling
  • Dataset Versioning
  • Data Lineage
  • Data Quality
  • Object Storage
  • Schema Design
  • APIs
  • Streaming Systems
  • Video Pipelines
  • Point Clouds
  • Time-Series Databases
  • ROS Bags
  • MCAP
  • Parquet
  • HDF5
  • Imitation Learning

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