Senior AI/ML & Robotics Platform Engineer

Job summary

Siemens is seeking a Senior AI/ML & Robotics Platform Engineer to define the data and validation backbone for a Physical AI platform in Canada. The role involves collaborating with various stakeholders to ensure robotics data is structured and aligned with AI needs, while also contributing to the development of validation pipelines and quality checks.

Qualifications

• Master’s degree or equivalent experience in Computer Science, Robotics, Machine Learning, Data Engineering, Artificial Intelligence, or a related field
• Strong experience in Python and modern data engineering or ML tooling
• Experience working with structured and unstructured datasets, metadata, validation workflows, and quality management
• Good understanding of AI/ML workflows, robotics data, perception data, or model evaluation pipelines
• Ability to bridge technical detail across software, data, and AI teams
• Strong analytical and problem-solving skills
• Practical mindset and willingness to work in ambiguous, early-stage platform environments

Responsibilities

• Define robotics dataset structures, metadata schemas, quality rules, and validation logic for industrial data collection and AI enablement
• Help design how robot state, action data, task context, vision streams, annotations, and environmental metadata are captured and represented
• Drive approaches for dataset versioning, reproducibility, lineage, and training/evaluation readiness
• Support the design of VLA-related data collection and Level 3 skill enablement interfaces
• Develop validation pipelines and quality checks for robotics data completeness, alignment, synchronization, and usability
• Work with research-facing stakeholders to translate model and evaluation needs into practical platform requirements
• Support handoff patterns between data collection, governance, review workflows, and downstream AI/ML consumers
• Collaborate with robotics integration engineers on practical semantics for robot episodes, sensor timelines, and action representations
• Help establish evaluation-ready datasets, benchmarking inputs, and structured feedback loops between platform and AI development
• Contribute code, prototypes, tooling, and technical guidance across platform and data workflows

Skills

Relocation