About the role

  • Design and implement LLM-based or transformer architectures for CAD-related reasoning tasks.
  • Develop reinforcement learning (RL) and supervise fine-tuning pipelines using real design data.
  • Build and maintain scalable data processing and evaluation frameworks.
  • Collaborate with CAD and software engineers to integrate ML outputs into real CATIA workflows.
  • Research and prototype AI methods for 3D scene understanding, graph-based optimization, and geometric reasoning.
  • Document results and present outcomes to technical and management stakeholders.
  • Create and maintain technical documentation and reports.
  • Ensure proper archiving of all relevant documents and data.

Requirements

  • M.S. or Ph.D. in Computer Science, Machine Learning, Robotics, or related field.
  • 2+ years of experience in applied ML, preferably with LLMs, RL, or geometric reasoning.
  • Strong programming skills in Python (PyTorch, TensorFlow, HuggingFace).
  • Solid understanding of 3D data, geometry, or CAD systems is a plus.
  • Familiarity with engineering data (e.g., wiring harness, manufacturing design) is beneficial.
  • Excellent communication and teamwork skills.
  • Additional experience and/or qualifications in the field of electrical engineering, automotive engineering, mechatronics or comparable qualifications are an advantage.
  • Experience in project management and coordination of development projects.
  • Proven experience coordinating a small engineering team.
  • In-depth knowledge of Design Release processes.
  • Experience with CAD systems and software (e.g. CATIA V5, 3DX, NX).
  • Knowledge of the relevant norms and standards in the automotive industry.
  • Ability to identify process improvements – eliminating waste and increasing efficiency.
  • Contribute to team knowledge base by sharing best practices across the organization.
  • Strong communication skills in English (written / verbal).
  • Additional ability to communicate in German is an advantage.

Benefits

  • 21 days’ vacation per calendar year, increasing yearly by 3 days to a maximum of 30 days.
  • Paid Holidays – 13 per year
  • Top notch medical, dental and vision insurance with Employer 50% contribution
  • Retirement plan
  • Performance bonuses
  • On-Site amenities (free coffee, equipped kitchen, parking reimbursement)
  • Two team events per year (summer / winter)
  • Internal training program
  • Employee development plan
  • High-quality IT equipment
  • Hybrid working possible after initial onboarding and probation.

Job title

AI / Machine Learning Engineer

Job type

Experience level

JuniorMid level

Salary

Not specified

Degree requirement

Postgraduate Degree

Location requirements

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