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Neura Robotics

Cognitive robots with perception, manipulation, collaboration

Integration & Distributed Systems Engineer - Cognitive Twin, Human

Backend EngineeringConfirmed live in the last 24 hours
Full-timeNo salary listedIn-person

About the Job

Requirements

  • A university degree (Bachelor's or Master's) in Computer Science, Robotics, Electrical Engineering, or a related field, or equivalent hands-on experience.
  • Several years of relevant experience designing and operating distributed, real-time systems and APIs/SDKs, with a track record of hardening research or prototype code into production services.
  • Strong modern C++ (C++17), with Python for tooling, and production-quality, tested code.
  • A solid grasp of inter-process communication, networking (TCP/IP), and real-time constraints.
  • Experience with robotics middleware (ROS 2 Humble, Fast DDS) and high-throughput transport (gRPC/Protobuf), plus schema-based serialization and code generation (binary schemas such as Protobuf) and multi-language SDK generation.
  • Experience with real-time streaming (WebRTC, WebSockets).
  • Comfort with containerized deployment and orchestration (Docker, Kubernetes, Linux).
  • Working familiarity with modern web development technologies (TypeScript and a framework such as React) and how they consume the API.
  • Familiarity with AI coding tools (e.g. Claude Code, Cursor, Copilot) and agentic orchestration for development.
  • A product-development mindset, adaptability as product requirements evolve, a structured working style, team spirit, and clear technical communication.
  • Perfect command of English.

Responsibilities

  • Design the API-first architecture and distributed communication layer of the Cognitive Twin, including transport, a real-time bidirectional sync loop, and a symmetric control plane for virtual and physical robots.
  • Design the transport using gRPC/Protobuf microservices, compact binary real-time frames, and WebRTC media/data streaming, and build the low-latency, high-throughput bidirectional telemetry sync loop between live fleets and the twin.
  • Build and maintain a single command path so the same controls drive virtual and live targets identically and remain consistent under load.
  • Build connectors and real-time links that keep the twin and its simulator in sync with robots, controllers, and surrounding services, including device-data ingestion with Fast DDS.
  • Design and own the cross-cutting API/SDK layer, generating language-agnostic SDKs from the scene definition format so the twin engine embeds into external developer environments.
  • Set deployment standards for service boundaries, backpressure, failure and reconnection semantics; instrument transport for latency and throughput; and harden services under load.
  • Own the binary data-exchange schema and scene definition format as the shared boundary between frontend, SDKs, and simulation backend, as well as SDK ergonomics, the programmatic-access authentication model, and backward-compatibility policy.

Desired Qualifications

  • Experience with gRPC-Web/Envoy, CI/CD and release engineering for distributed services, software for real robots including control loops, device drivers and middleware, or open-source robotics/middleware contributions.
  • German language skills.

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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