AI/ML Engineer (m/f/d) Autonomous Systems

MOTOR Ai; Berlin; On-site; Vertraulich; Full time

Benefits offered by this job

Focus on people

Genuine team spirit

Professional development costs covered

Flexible working hours

Corporate discounts

Social relevance

Public transport subsidy

Excellent transport links

Job summary

MOTOR Ai is advancing Level 4 autonomous driving in Germany. We design and deploy cutting-edge AI models, turning research into product features for real-time autonomous systems. Our team collaborates across data, perception, and simulation disciplines to validate models on real-world-like scenarios.

We seek engineers with hands-on AI/ML expertise, strong Python and DL tooling skills, plus a drive to innovate in automotive AI and software integration. German language skills are a plus.

Qualifications

• Completed degree in computer science, machine learning, data science, or equivalent.
• 3+ years hands-on AI/ML engineering experience.
• Strong knowledge of deep learning; reinforcement learning; automotive domain experience a plus.
• Strong Python skills with ML frameworks (PyTorch and/or TensorFlow).
• Experience with reinforcement learning tooling (Stable-Baselines3, RLlib) and experiment-tracking tools (MLflow, Weights & Biases).
• Experience deploying models for production/real-time systems (ONNX, TensorRT, C++ integration).
• Solid engineering practices: Git, CI/CD, and containerization (Docker, Kubernetes).
• Comfort with cloud compute (AWS, GCP, Azure) and data tooling (NumPy, Pandas, SQL); CARLA/ROS a plus.
• English C1 required; German a plus; valid driving license.

Responsibilities

• Model Development & Training - Design, train, and fine-tune ML models for autonomous driving use cases.
• Model Deployment & Integration - Integrate trained models into production systems for reliable operation.
• Experimentation & Evaluation - Run structured experiments and evaluations using established benchmarks.
• Performance Optimization - Optimize models for latency, memory, and compute in real-time systems.
• Cross-Functional Collaboration - Partner with data, perception, and simulation teams to validate data and scenarios.

Skills

Python

Deep Learning

Reinforcement Learning

ML Engineering

Cloud/GPU

Education

Degree in CS/ML or related

Tools

PyTorch

TensorFlow

ONNX

TensorRT

Docker

Kubernetes

Job description

We are MOTOR Ai. Our mission is to make Level 4 autonomous driving a reality in Germany and beyond. By combining state-of-the-art AI with the expertise of our multidisciplinary team, we are poised to introduce the first solution of its kind in Germany that is eligible for certification on European roads. Since 2017, we have been steadfastly pursuing a single goal: to shape a future that is already in motion.

Tasks

• Model Development & Training - Design, train, and fine-tune machine learning models to meet performance, accuracy, and robustness requirements for autonomous driving use cases
• Model Deployment & Integration - Integrate trained models into production systems, ensuring reliable, efficient, and safe operation within the overall software stack
• Experimentation & Evaluation - Run structured experiments and evaluations to validate model performance, using established metrics and benchmarks
• Performance Optimization - Optimize models for latency, memory, and compute constraints relevant to real-time autonomous systems
• Cross-Functional Collaboration - Partner with data, perception, and simulation teams to ensure models are built on the right data and validated against real-world scenarios

Requirements

• A completed degree in computer science, machine learning, data science, or a comparable field - or equivalent vocational training/apprenticeship in a relevant technical discipline. Hands-on experience counts at least as much as the formal qualification
• 3+ years of relevant hands-on experience in applied AI/ML engineering
• Strong knowledge of deep learning and reinforcement learning; familiarity with Active Inference approaches is a plus. Experience in the automotive industry and a track record of turning research papers into working product features are both an advantage
• Strong Python skills with solid ML fundamentals, and hands-on experience with deep learning frameworks (PyTorch and/or TensorFlow)
• Experience with reinforcement learning tooling (e.g. Stable-Baselines3, RLlib) and experiment-tracking tools (e.g. MLflow, Weights & Biases)
• Experience deploying and optimizing models for production/real-time systems (e.g. ONNX, TensorRT, C++ integration)
• Solid engineering practices: Git, CI/CD pipelines, and containerization (Docker, ideally Kubernetes)
• Comfortable working with cloud/GPU compute environments (AWS, GCP, or Azure) and data tooling (NumPy, Pandas, SQL); experience with simulation environments such as CARLA and ROS/ROS2 familiarity are both a plus
• An open-minded, curious mindset - you enjoy trying new approaches and ideas
• A valid driving license
• English C1 is required; German is a plus

Benefits

• Focus on people: Our strength lies in our diversity. We respect each other for who we are
• Genuine team spirit: working in teams that drive change forward – no matter how complex and extensive the projects are
• Your professional development is important to us – that's why we cover the costs of further education and training
• Flexible working hours – with room for the realities of life (parenthood, caregiving responsibilities, voluntary work, etc.)
• Whether it's fashion, beauty, travel or culture – you'll receive numerous discounts through our partner Corporate Benefits
• Social relevance: We work on solutions that have game-changing qualities
• Subsidy for public transport tickets
• Excellent transport links: attractive location in Wedding with very good public transport connections

At our new premises, we place great importance on getting to know one another and working together to drive our vision forward. Our international team is growing and working together on this exciting mission. Face-to-face collaboration is the key to success, which is why we have decided not to become a fully remote company.