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

Synapticon

Schönaich, GermanyFull-time / InternshipPosted 3mo agoStill listed 3 days ago

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At a glance

Compensation
No compensation found
Location
Schönaich, Germany
Role Type
Internship
Schedule
Full-time / Internship
Work Authorization
Not specified

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Requirements

Credentials this posting asks for.

Bachelor's degree

Job overview

Synapticon seeks a motivated AI/ML Engineering Intern to join its Safety AI team in Schönaich for a six‑month, mandatory internship. The role involves researching and prototyping multimodal foundation model integration, developing AI‑based fall strategy controllers, and implementing real‑time ML inference for humanoid robots, with flexible start dates and working hours.

Skills & qualifications

RequiredNice to have

Skills

Machine LearningReinforcement LearningLinear AlgebraProbabilityPyTorchStable Baselines3Isaac LabROS2OptimisationFoundation Model Fine‑Tuning

Qualifications

Enrolled MSc Student in Machine Learning, Computer Science, or Robotics

Full job description

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.

  • 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

  • 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

  • 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)

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