Senior Machine Learning Engineer (m/f/*)

• Design, train, and optimize deep learning models for object detection, semantic segmentation, pose estimation, and tracking.
• Port and deploy models to resource-constrained edge hardware, achieving single-digit millisecond latency without cloud dependencies.
• Build and maintain robust vision pipelines from data ingestion through training to production inference.
• Apply model compression techniques such as quantization, pruning, knowledge distillation, and neural architecture search to meet strict performance budgets.
• Develop synthetic data and domain adaptation pipelines to close the sim-to-real gap.
• Profile inference pipelines end-to-end to identify and eliminate bottlenecks on target silicon.
• Translate cutting-edge academic research into highly reliable, production-grade systems.
• Collaborate closely with hardware, product, and research colleagues to shape our privacy-by-design architecture.
• Requirements
• Your Profile
• Core Competencies: Computer Vision & Edge AI

• Edge AI & On-Device Inference: Expertise in porting, deploying, and optimizing complex deep learning models for local, resource-constrained hardware without cloud dependencies.
• Advanced Computer Vision: Deep knowledge of developing vision pipelines for object detection, semantic segmentation, pose estimation, and tracking.
• Hardware-Aware Architecture Design: Ability to custom-build network topologies tailored to specific sensors and strict latency budgets, rather than relying on off-the-shelf APIs.
• Synthetic Data & Domain Adaptation: Proven experience in building simulation pipelines for synthetic data generation and closing the “sim-to-real” gap using Domain Randomization and GANs. Technical Stack & Tools
• Languages: Advanced proficiency in C++ (for production-grade edge deployment) and Python (for training, research, and data analysis).

AI/ML Frameworks: Extensive hands-on experience with PyTorch, and TensorFlow / Keras. Optimization & Deployment: Mastery of inference acceleration and model conversion using TensorRT, ONNX, and OpenVINO. Model Compression: Practical application of quantization, pruning, knowledge distillation, and neural architecture search. System Architecture & Compliance Privacy-by-Design Architecture: Designing robust, local AI systems that guarantee data sovereignty and strict GDPR compliance without cloud roundtrips. Performance Profiling: Deep-dive auditing of inference pipelines to identify bottlenecks and achieve single-digit millisecond latency on target silicon. Research, Strategy & Leadership Research-to-Production (R2P): The ability to translate complex, state-of-the-art academic research into highly reliable systems that work in the real world. AI Strategy & Assessment: Capability to conduct feasibility studies, ROI analysis, and privacy-first architecture blueprinting. Mindset Comfort with ambiguity, a problem-solving mindset, and adaptability to rapid change. Entrepreneurial drive, a strong sense of responsibility, high ambition, and a collaborative approach to achieving goals. Excellent verbal and written communication skills in English and the ability to effectively collaborate with various stakeholders. Having work experience in a startup or venture capital is a plus. We don’t expect anyone to check all these boxes mentioned above! If a few of these points apply to you, we want to talk! We offer Benefits Our offering

• The opportunity to significantly contribute to the company's growth and success.
• A competitive salary.
• An evolving role that grows with our company's journey.
• We have flexible working hours and a need-based work-from-home policy; all processes are being set up for remote first.
• A diverse and inclusive work environment as well as a flat organizational structure, fast decision making within the team, disagree & commit.

We foster a culture where we all learn from each other and value new ideas. We hold fun team events throughout the year. We contribute to your monthly public transport ticket. Free drinks, snacks, and coffee.