Senior/ Staff Data Platform Engineer (F/M/D)

The Opportunity

We’re looking for a Senior/ Staff Data Platform Engineer to architect and scale the data backbone powering next-generation AI models in robotics and real-world environments.

This role sits at the intersection of distributed systems, multimodal data processing, and applied machine learning, with a strong focus on building high-quality datasets for robotic foundation models. You will ensure that data pipelines, infrastructure, and data strategy directly translate into measurable improvements in model performance.

Your Responsibilities

• Drive the model–data loop by connecting application requirements with data collection, and translating model failures into data-driven improvements through collection, curation, and augmentation
• Build and scale distributed data pipelines (Ray/Anyscale or similar) for TB-scale video, sensor, and robotics datasets
• Own dataset quality and coverage, including annotation workflows, data diversity, and storage trade-offs
• Build and lead a small team in the future and coordinate with data providers and annotation vendors
• In the future, oversee real-world data collection, including technical setup, compliance, and secure data handling

Technologies

• Python (advanced, production-grade)
• Ray / Anyscale or Apache Spark
• AWS / GCP for large-scale data and GPU training pipelines
• Video and sensor data formats (H.264/H.265, ROS bags, MCAP)
• PyTorch, NumPy
• DVC, LakeFS or similar data versioning tools
• Distributed data processing and storage systems

Requirements

Must Have

• 8+ years in Data/ML Engineering, including 4+ years in a senior or lead role
• Experience with large-scale real-world data (robotics, autonomous systems, or video AI)
• Experience designing multimodal data schemas aligning video, actions, and high-frequency sensor streams
• Strong experience with Ray/Anyscale or Spark for distributed pipelines
• Advanced Python (performance, concurrency, ML stack like NumPy/PyTorch)
• Experience working with video and sensor data formats (e.g., H.264/H.265, ROS bags, MCAP)
• Experience building scalable data pipelines for GPU-based training workloads (AWS/GCP)
• Experience with data versioning tools such as DVC or LakeFS
• Proven experience owning systems and mentoring engineers

Nice to Have

• Experience building datasets for multimodal foundation models (VLA, VLM or similar)
• Robotics fundamentals (sensor synchronization, 3D transforms)
• Experience with active learning or data-centric ML workflows

Benefits