Stellenangebot: Senior Software Engineer – Robotics, Distributed Systems & ML Infrastructure (m/f/d)

RobCo steht an der Spitze einer Revolution in der Robotik, die es Unternehmen ermöglicht, ihre Produktivität zu steigern und sich vom Arbeitskräftemangel zu befreien. Wir suchen Dich, um RobCo zum führenden Robotikunternehmen in Europa und den USA zu machen. Wir haben mehr als 50 Millionen Dollar von den weltbesten Risikokapitalgebern wie Sequoia Capital und Lightspeed sowie den Gründern von UiPath, Helsing, Pitch und weiteren Firmen erhalten, um unsere Mission zu erfüllen.

Bei RobCo erfolgt die Auswahl von Bewerber*innen unabhängig von ethnischer Herkunft, Religion, Geschlecht, Alter, Behinderung oder sexueller Orientierung. Alle Entscheidungen im gesamten Rekrutierungsprozess basieren ausschließlich auf den Qualifikationen, Fähigkeiten, Kenntnissen und Erfahrungen der Bewerber*innen sowie den relevanten Geschäftsanforderungen.

As a Senior Software Engineer in our Autonomy & Learning team, you will build the software foundations that enable next-generation robot autonomy at scale. You will work across robot middleware (ROS 2), distributed systems, cloud infrastructure, and ML data pipelines to create reliable, high-performance components that power robotic learning, deployment, and real-time operation.

This role blends deep engineering craftsmanship with systems-level thinking. You will own critical architectural decisions, collaborate closely with autonomy, controls, and ML teams, and help shape the technical backbone of RobCo’s next-generation robotic platform.

Your Responsibilities

• Build autonomy platform components - Design and implement high-quality services and modules in a ROS 2–based robotics system with tight latency constraints and high quality of service.

• Develop distributed robotic systems - Architect control, perception, and telemetry pipelines that integrate tightly with real robot hardware.

• Drive ML data pipelines - Develop ingestion, preprocessing, and storage pipelines for multimodal datasets; support large-scale training workflows.

• Cloud & distributed infrastructure - Build on top of our scalable cloud-native systems (AWS) including data flows, EC2 orchestration, containerized services, and compute clusters.

• Enable scalable robot learning - Integrate technologies such as Ray/Anyscale for distributed training, simulation, rollout generation, and model evaluation.

• Deliver engineering excellence - Lead code reviews, testing strategies, CI/CD, observability, and documentation standards.

• Collaborate cross-functionally - Work with autonomy, controls, and ML teams to define system interfaces and ensure seamless integration.

• Mentor & lead – Provide technical guidance, make architectural decisions, and elevate the engineering culture.

• 5–10+ years of experience in software engineering, distributed systems, or robotics platforms

• Aptitude for dealing with and optimizing performance-critical systems and algorithms

• Strong proficiency in C++ and Python, with clean, maintainable engineering practices

• Deep experience with ROS 2 and Zenoh (nodes, messaging, lifecycle, middleware, performance, real-time systems)

• Hands-on experience building distributed systems, including messaging, compute orchestration, and storage

• Strong knowledge of Docker, container runtimes, and cloud environments (AWS preferred)

• Experience with PyTorch or ML toolchains and familiarity with data workflows (Ray, Spark, or similar)

• Solid system design skills and ability to own complex architectural components end-to-end

• Excellent collaboration skills and ability to work across autonomy, ML, and robotics engineering domains

• Experience with front-end development a plus
  

• Shape the architecture of a full robotics autonomy stack - from edge devices to cloud-scale learning infrastructure

• Work with a world-class robotics and ML team pushing the frontier of modular autonomy

• High ownership, deep technical impact, and the ability to influence foundational design decisions

• Hybrid work model, flexible hours, and top-tier equipment

• A transparent, high-trust environment with rapid learning and growth opportunities