Platform Engineer – Robot Data Infrastructure (human) at Neura Robotics (Metzingen, Germany / Riederich, Germany)
Neura Robotics· Metzingen, Germany / Riederich, Germany·
Role details
Neura Robotics at a glance
German cognitive-robotics company building humanoid and collaborative robots that see, hear, feel, and learn to work alongside people.
NEURA Robotics designs cognitive robots (humanoids, collaborative arms, and mobile bases) plus the AI and platform that run them, all built in-house. Its flagship 4NE1 humanoid targets industrial workflows and everyday assistance, and the Neuraverse platform links deployed robots into a shared learning network.
~$1.7B+ raised · latest: Series C · up to $1.4B · June 2026 · backed by Tether, Amazon, NVIDIA, Qualcomm
Summary
Design, implement, and maintain scalable ETL data pipelines and data models for robotics applications. The role involves ensuring data quality, governance, and security while collaborating with cross-functional teams to deliver high-quality datasets using modern data technologies.
Job description
Your mission & challenges
You design, build, and operate the end-to-end data infrastructure that turns raw multi-modal robot sensor recordings into ML-ready datasets. Working at the intersection of robotics, edge computing, and cloud data engineering, you own the full pipeline, from physical data collection environments to training-ready formats for robot learning.
- Data format & pipeline design: Define and evolve internal data formats for multi-modal sensor streams (video, depth, audio, point clouds, joint states, tactile) with efficient compression.
- Edge-to-cloud ingestion & transformation: Build services that orchestrate on-premise recording, validate data quality, transfer large volumes to the cloud, and convert raw data into structured formats for ML consumption.
- Infrastructure automation: Provision and manage on-premise compute via infrastructure-as-code, and handle containerized deployments and rolling updates across distributed sites.
- Platform services & tooling: Develop backend services (TypeScript, Python), shared libraries, CLI tools, and developer documentation.
- Multi-agent annotation: Orchestrate vision-language agents that auto-annotate multi-modal episodes at scale, with human-in-the-loop review to keep labels training-ready.
- Cross-functional collaboration: Work closely with hardware, robotics, and AI/data science teams to onboard new sensor modalities and track data throughput KPIs.
What you bring:
- Backend engineering: Strong Python and TypeScript skills in production backend systems.
- Cloud: Hands-on cloud experience, AWS preferred.
- Robotics middleware: Experience with ROS 2/DDS or similar robotics middleware.
- Media codecs: Familiarity with video/audio codecs and compression (FFmpeg, PyAV, H.264/AV1).
- Infrastructure-as-code: Ansible, Docker, and Terraform for fleet management.
- DevOps mindset: You care about CI/CD, automation, and keeping things shippable.
- ML data pipelines: Interest in or exposure to ML data pipelines and robot learning.
Why work at Neura Robotics
- Culture: "Passion for Winning" — achievement-driven, self-responsible culture with flat hierarchies. Values include trust, honesty, speed, and "We Are Human" (people at the heart of everything).
- Flexibility: Flexible working hours, 30 days of vacation, and a hybrid-friendly environment.
- Team: Over 1,400 employees from more than 45 countries — highly skilled, international team of experts.
- Growth & Development: Support for personal and professional growth via Udemy training platform and more.
- Compensation: Competitive salary package with exclusive employee discounts.
- Perks: Summer parties, company town hall meetings, and regular team celebrations.
- Impact: Opportunity to work on cutting-edge cognitive robotics and AI that directly addresses labor shortages and makes a meaningful societal impact.
- Diversity: Explicitly welcomes applications from all backgrounds, emphasizing building a team that reflects the world.
- Application Process: Fast — initial feedback within a few days, interviews scheduled within two weeks.