Neura Robotics

Cognitive robots with perception, manipulation, collaboration

Platform Engineer - Robot Data Infrastructure

Platform EngineeringConfirmed live in the last 24 hours

Full-timeNo salary listedIn-person

About the Job

Requirements

Strong Python and TypeScript skills in production backend systems.
Hands-on cloud experience; AWS is preferred.
Experience with ROS 2/DDS or similar robotics middleware.
Familiarity with video/audio codecs and compression, such as FFmpeg, PyAV, H.264, or AV1.
Experience using Ansible, Docker, and Terraform for fleet management.
Interest in or exposure to machine-learning data pipelines and robot learning.

Responsibilities

Design, build, and operate end-to-end data infrastructure that turns raw multimodal robot sensor recordings into machine-learning-ready datasets, owning the pipeline from physical data collection environments to training-ready formats for robot learning.
Define and evolve internal data formats for multimodal sensor streams, including video, depth, audio, point clouds, joint states, and tactile data, with efficient compression.
Build services to orchestrate on-premise recording, validate data quality, transfer large volumes to the cloud, and convert raw data into structured formats for machine-learning consumption.
Provision and manage on-premise compute using infrastructure as code, and handle containerized deployments and rolling updates across distributed sites.
Develop backend services, shared libraries, command-line interface tools, and developer documentation.
Orchestrate vision-language agents to automatically annotate multimodal episodes at scale, with human-in-the-loop review to keep labels training-ready.
Work with hardware, robotics, and AI/data science teams to onboard new sensor modalities and track data-throughput key performance indicators.

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.

About the Company

Neura Robotics

Cognitive robots with perception, manipulation, collaboration

Neura Robotics builds cognitive robots for industrial and service settings, combining perception, manipulation, and human collaboration. It develops both the hardware and the software stack for Physical AI, creating robot platforms like MAiRA, MAV, LARA and MiPA along with training infrastructure. The system works by integrating sensing, decision-making, and manipulation capabilities on a hardware-software stack that can be deployed in large-scale production, with the company planning robots fleets and NEURA Gyms for ongoing training and improvement. What sets Neura Robotics apart is its end-to-end approach to Physical AI, including a focus on mass production, an established global deployment plan, and a broad ecosystem of strategic backers and partners that support scaling and international expansion. The goal is to enable worldwide deployment of its robot platforms and associated training infrastructure, turning physical AI into widely available industrial and service automation.

Company size: 501-1,000
Company stage: Series C
Total funding: $1.7B
Headquarters: Metzingen, Germany
Founded: 2019

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