AI Developer

Munich | Up to €120,000 | Onsite 3–4 days per week

AI gets a lot harder when it has to work in the physical world.

I'm working with an exciting Munich-based robotics AI company that is building technology to help robots understand and manipulate soft, flexible materials that traditional automation has struggled with for decades.

These objects move, fold, stretch, deform and behave differently every time.

For humans, handling them feels natural.

For robots, it is one of the harder problems in real-world automation.

The company is already deploying robotic systems in production and is now scaling the AI platform behind them. This is a chance to work on physical AI that does more than perform well in controlled experiments. It needs to work on real robots, under real production constraints, at industrial speed.

The role

As an AI Developer, you will work on the core AI systems behind a deployed robotics platform.

You will build and improve deep learning models for computer vision and manipulation, develop ML pipelines, improve model reliability, and help take AI systems from experiment through to production.

This is not a clean research role where success only means a better benchmark.

The work involves noisy data, edge cases, broken assumptions, production constraints and real-world failure modes. The right person will enjoy that.

What you will be working on:

• Building AI systems that run on real robotic systems in production
• Developing deep learning models for computer vision and robotic manipulation
• Working with Python, PyTorch and modern ML engineering workflows
• Designing and maintaining ML pipelines across training, evaluation and deployment
• Improving experiment tracking, reproducibility and model lifecycle discipline
• Increasing model robustness across real-world noise and edge cases
• Automating training workflows and model iteration loops
• Working closely with robotics, MLOps and simulation teams
• Helping shape a production-grade Physical AI platform

What they are looking for

The strongest fit will likely be someone with a strong academic and technical foundation, ideally including a PhD or research background from a leading university, combined with practical experience building computer vision or machine learning systems that work beyond controlled experiments.

You should bring experience across several of the following areas:

• 2–4+ years of experience in computer vision, deep learning or applied machine learning
• Strong Python and PyTorch fundamentals
• Experience with object detection, classification, segmentation or related CV tasks
• Understanding of model training, evaluation, failure modes and robustness
• Experience with ML pipelines, cloud infrastructure or MLOps tooling
• Familiarity with tools such as ClearML, GCP or similar ML infrastructure
• Ability to move quickly without needing perfect structure

Useful additional experience

• Robotics, industrial AI or embodied AI experience
• Experience with manipulation, grasping or scene understanding
• Vision-language models or foundation model exposure
• Experience productionising machine learning solutions
• Exposure to simulation, synthetic data or sim-to-real workflows

Culture fit

This is an important part of the search. They are looking for someone sharp, ambitious and intrinsically motivated, but also humble enough to reflect honestly on where they are, where they want to go and what they still need to improve.

The right person will take ownership of their technical area, stay close to the problem and care about building something genuinely difficult.

Not someone who oversells.

Someone who wants to achieve something meaningful and is prepared to do the hard engineering work required to get there.

Logistics and Package

• Working model: Onsite 3–4 days per week
• Salary: Up to €120,000, depending on experience
• Additional package: Competitive benefits including equity participation
• Visa: Candidates must already have the right to work in Germany. EU citizens or permanent residents in Germany are strongly preferred. Visa sponsorship is not available for this search.

Why this is worth considering

This is a chance to work on one of the more interesting problems in robotics: getting AI to understand and interact with materials that are difficult to model, predict and control.

The work is technical, applied and directly connected to deployed robotic systems.

If you want a role where computer vision, physical AI, ML infrastructure and robotics come together, this is a strong opportunity to explore.

If this sounds relevant, apply here or message me directly and I can share more context on the company, team and process.