Platform Engineer – Robot Data Infrastructure (human)

Neura Robotics; München; Hybrid; EUR 70,000 - 110,000; Full time

Job summary

Neura Robotics in Munich is seeking an experienced Backend Data Infrastructure Engineer to design, build, and operate end-to-end data pipelines. You will turn raw multi-modal robot sensor recordings into ML-ready datasets and own the pipeline from data collection environments to training-ready formats for robot learning.

You'll work across robotics, edge computing, and cloud data engineering, collaborating with hardware, robotics, and AI/data science teams to onboard new modalities and ensure

Qualifications

• Backend systems in production using Python and TypeScript.
• Cloud experience with AWS preferred.
• Experience with ROS 2/DDS or similar robotics middleware.
• Familiarity with video/audio codecs and compression (FFmpeg, PyAV, H.264/AV1).
• Infrastructure-as-code tools: Ansible, Docker, Terraform.
• DevOps mindset emphasizing CI/CD and shipping features.
• Interest in ML data pipelines and robot learning.

Responsibilities

• Design and evolve data formats for multi-modal sensor streams.
• Build edge-to-cloud ingestion and data transformation services.
• Automate infrastructure and fleet management with IaC and containers.
• Develop backend services and tooling (CLI, libraries).
• Oversee multi-agent annotation pipelines with human-in-the-loop reviews.
• Collaborate with hardware, robotics, and AI/data science teams.

Skills

Python

TypeScript

CI/CD

DevOps mindset

ML data pipelines

Tools

ROS 2/DDS

FFmpeg

PyAV

H.264/AV1

Ansible

Docker

Terraform

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.