At least 8 years of experience in data or machine learning engineering, including at least 4 years in a senior or lead role.
Experience with large-scale real-world data in robotics, autonomous systems, or video AI.
Experience designing multimodal data schemas that align video, actions, and high-frequency sensor streams.
Strong experience with Ray/Anyscale or Apache Spark for distributed pipelines.
Advanced Python skills, including performance, concurrency, and machine learning libraries such as NumPy and PyTorch.
Experience working with video and sensor data formats such as H.264/H.265, ROS bags, and MCAP.
Experience building scalable data pipelines for GPU-based training workloads using AWS or GCP.
Experience with data versioning tools such as DVC or LakeFS.
Proven experience owning systems and mentoring engineers.
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 for terabyte-scale video, sensor, and robotics datasets using Ray/Anyscale or similar tools.
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.
Desired Qualifications
Experience building datasets for multimodal foundation models such as VLA or VLM.
Robotics fundamentals, including sensor synchronization and 3D transforms.
Experience with active learning or data-centric machine learning workflows.
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
Competitive compensation package
Various employee subsidies and perks, including public transportation and Wellpass
Work with a world-class team in a flat hierarchy, with direct collaboration alongside the founders and engineering team
Opportunity to make a real impact by working on cutting-edge robotics and AI systems
Fast growth potential in a rapidly evolving company and industry
International office environment with English as the official working language
Recruiting Process
Your recruiting partner for this role is Madhulika (she/her). The process includes a screening interview, two virtual technical interviews, and an onsite visit to our office in Munich to meet with the team.
We hire across backgrounds, identities, and experiences, and we are committed to a workplace where everyone belongs. Discrimination has no place here.
If you need any accommodations during the recruiting process, just reach out to your recruiting partner.