Siemens

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

Siemens • $90K — $110K *
Technical Services
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • Bachelor's or Master's degree in Computer Science, Data Engineering, Robotics, or related field.
  • 3+ years of experience in building data pipelines or high-volume event-based storage.
  • Strong programming skills in Python; experience with SQL and data formats.
  • Experience with time-synchronized, multimodal, or high-frequency data handling.
  • Understanding of data lineage, versioning, and privacy controls.
  • Ability to define data-quality checks for various data integrity issues.
  • Experience supporting labeling and curation workflows.

Responsibilities

  • Build data pipelines for teleoperation sessions and robot state.
  • Define schemas for synchronized multimodal robotics episodes.
  • Implement workflows for event-based data capture and validation.
  • Support data curation, labeling, and quality reporting.
  • Create checks for data quality issues like timing drift and missing metadata.
  • Collaborate with engineering teams on evaluation corpora and failure analysis.
  • Define governance for data retention and separation.

Benefits

  • Hybrid work environment with on-site collaboration for data collection.
  • Hands-on experience with cutting-edge robotics technology.
  • Opportunity to work on impactful projects in AI and robotics.
  • Access to a supportive team focused on innovation and quality.
Full Job Description
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

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.

#LI-Hybrid

About Siemens

Siemens AG is a German multinational conglomerate company headquartered in Munich and the largest industrial manufacturing company in Europe with branch offices abroad. The principal divisions of the company are Industry, Energy, Healthcare, and Infrastructure & Cities, which represent the main activities of the company. The company is a prominent maker of medical diagnostics equipment and its medical health-care division, which generates about 12 percent of the company's total sales, is its second-most profitable unit, after the industrial automation division. The company is a component of the Euro Stoxx 50 stock market index. Siemens and its subsidiaries employ approximately 385,000 people worldwide and reported global revenue of around €87 billion in 2019 according to its earnings release.
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