FLEXOO makes Physical AI possible.
We develop and manufacture a scalable technology platform that combines ultra-thin, freely moldable sensors with real-time data processing at the edge—thereby creating the physical data foundation for modern industrial systems. Our expertise in printed electronics forms the technological basis for this.
As a deep-tech company based in Heidelberg, we combine development, industrial manufacturing, and application expertise—with a clear focus on translating technologies into scalable applications.
Join our innovative development team and shape the future of intelligent technology as an AI Engineer (m/f/d), where your ideas turn cutting-edge research into real-world impact.
Your Tasks
- Design and implement end-to-end AI pipelines for time-series and event-driven sensor data across battery and robotics applications
- Combine physics-based models with data-driven approaches, hybrid and physics-informed machine learning to build systems that are robust, interpretable, and certifiable for industrial deployment
- Deploy and optimize AI models on embedded and edge hardware, from microcontrollers to edge gateways, with hard latency and memory constraints
- Collaborate closely with hardware, firmware, and systems engineers to integrate sensor electronics, data acquisition, and AI inference into real devices
- Develop, validate, and benchmark models for state estimation, anomaly detection, fault classification, and remaining useful life prediction in both battery management and robotic manipulation contexts
Your Profile
- Master's degree or PhD in Computer Science, Robotics, Electrical Engineering, Applied Mathematics, or a related field
- 3+ years of applied machine learning experience, ideally for sensor-based systems in robotics, industrial automation, or energy storage
- Strong Python and C++ skills; practical experience with PyTorch ; JAX experience is a plus for physics-informed modelling
- Proven experience deploying models to embedded or edge targets; familiarity with edge deployment pipelines (ONNX, TensorFlow Lite, or equivalent)
- Solid understanding of time-series data engineering: synchronization, cleaning, labeling, and handling of large continuous sensor streams
- Experience with at least two of: reinforcement learning, imitation learning, multimodal foundation models, or physics-informed neural networks
- Familiarity with cloud infrastructure and CI/CD for ML systems (MLOps)
- Published research in machine learning, robotics, or sensor intelligence at a leading venue is an advantage
- Proficiency in English and German
We offer
At FLEXOO, you can expect more than just a job — you will become part of an innovative environment where your ideas matter and your contributions are visible:
- You are part of a team of experts with the opportunity to shape next-generation AI functionality in sensor-rich systems such as battery storage solutions and robots
- You will closely collaborate with experts in printed electronics, embedded systems, and industrial monitoring
- We offer you a long-term position with room to grow into technical leadership for AI in sensor-based products
- Attractive and performance-based compensation in a future-oriented company
- Flexible working hours and the option to work remotely one day per week
- Various benefits (business lunch, free hot and cold drinks, job ticket, etc.)
- Regular team events
- Modern location in Heidelberg Bahnstadt, 10 minutes from the main train station, free parking
Ready to build the future?
Then apply by submitting your complete application documents — including your resume, cover letter, transcripts and employer references — directly through our website at www.flexoo.com > About Us > Career.
Any questions?
Feel free to reach out—we look forward to hearing from you.
Marion Lohnert | HR Manager | [email protected]
FLEXOO GmbH | Speyerer Str. 4 | 69115 Heidelberg | www.flexoo.com
Job Types: Full-time, Permanent
Pay: 55.000,00€ - 75.000,00€ per year
Experience:
- applied machine learning: 3 years (Required)
Language:
- English C1 (Required)
- German C1 (Required)
Work Location: Hybrid remote in 69115 Heidelberg
