Hiring.Camp

AI/ML Engineering Intern – Behavioral Safety (m/f/d)

Synapticon

·

Jun 12, 2026

Location
Schönaich, Baden-Württemberg
Type
Internship
Department
Engineering
Seniority
Internship
Source
Personio

Description

WHAT WE ARE LOOKING FOR

We're looking for a motivated AI/ML Engineering Intern (ideally 6 months, mandatory internship) to join our Safety AI team in Schönaich (close to Stuttgart), with a flexible start date. If you're excited about applying machine learning to genuinely open research questions in humanoid robotics — from semantic intent recognition to AI-based fall strategies — this is a rare opportunity to do research with a direct path to product.


HERE'S WHERE YOU MAKE AN IMPACT

  • Prototype multimodal foundation model integration for robot safety context — exploring how large-scale models can give robots semantic awareness of their environment and the people in it

  • Develop and test AI-based fall strategy controllers, working on one of the more genuinely open research questions in humanoid deployment

  • Implement ML model inference in the robot control loop — bridging the gap between research models and the timing constraints of real-time robot software

  • Benchmark behavioral safety classifiers for semantic intent recognition in simulation, building the evidence base for what these models can and can't reliably distinguish in deployment

  • Build evaluation frameworks for AI safety behaviour aligned with ISO/IEC TR 5469 — contributing to a principled, documented approach to assessing AI in safety-relevant contexts


WHO YOU ARE

  • Enrolled MSc student in Machine Learning, Computer Science, or Robotics — with a research mindset and the discipline to support it with rigorous, reproducible evaluation

  • Strong PyTorch skills; hands-on RL experience using Stable Baselines3, Isaac Lab, or similar frameworks — you've trained policies and analysed why they fail, not just run examples

  • You've integrated ML inference pipelines with ROS2 — or are confident you can make it work cleanly in a real-time control context

  • Experience with foundation model fine-tuning is a strong plus — this work involves adapting large models for a specific purpose, not just deploying them off the shelf

  • You're interested in safety-critical AI — not as a compliance checkbox, but as a genuinely hard technical and methodological problem

  • Strong mathematical foundation across linear algebra, optimisation, and probability — you're comfortable with the theory behind what you implement


WHAT'S IN IT FOR YOU

  • Flexible working hours when life takes unexpected turns

  • Company support for gym memberships through Wellpass

  • Birthday vouchers

  • Drinks and coffee (free of charge, of course)

  • Snacks and fruit for all employees, as well as breakfast every Monday

  • Regular global team-building events such as boot camps, skiing, and summer BBQs

  • An international team with long-term prospects

  • Highly competent colleagues who are experts in their field and happy to support you in your learning and growth

  • Modern office space

  • Our company's WG (upon availability)

Skills

Machine LearningPyTorchCompliance

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