Edge AI Engineer

• Model Design and Deployment: On-Device: Design, train, and validate ML models for computer vision, sensor fusion, signal processing, and predictive analytics
• Develop and optimize ML pipelines for on‑device inference, including quantization, power/performance tuning, and DSP/NPU acceleration
• Monitor, test, and optimize the performance of deployed models to ensure accuracy, scalability, and maintainability
• Data Processing & Analysis: Build data ingestion, preprocessing, and feature‑engineering pipelines for both edge and hybrid (Edge + Cloud) deployments
• Extract, process, and analyse large datasets to generate actionable insights and continuously improve model performance
• Collaboration: Work with cross‑functional teams—architects, embedded developers, PMs, UI/UX, and customers—to develop and integrate ML functionality into real products
• Participate in prototyping, PoCs, and contribute to customer dialogues and technical presentations
• Participate in technical discussions, document your work, and clearly explain the trade-offs and decisions behind the solutions you present
• Stay Current: Keep up to date with the latest trends, tools, and technologies in AI/ML to ensure our solutions are cutting-edge

• Strong hands‑on experience in Python, ML frameworks such as PyTorch or TensorFlow, and classical CV libraries (OpenCV, scikit‑learn)
• Ability to build and deploy ML models for Edge or Embedded platforms, preferably with experience on Qualcomm, Nordic, NXP, or similar SoCs
• Familiarity with quantization, model compression, benchmarking, and inference profiling on constrained hardware
• Experience with data pipelines, including data validation, augmentation, and performance analysis
• Understanding of end‑to‑end ML lifecycle, including experimentation, evaluation, and deployment in production environments
• Master’s or PhD in ML, Robotics, Autonomous Systems or related fields
• 2+ years of hands-on experience developing and deploying ML models in production
• Proven experience in one or more of: Computer vision
• Time‑series or sensor‑data ML
• LLM‑based or hybrid AI systems
• Effective communication skills and experience working in cross-functional teams
• Passionate about staying up to date with emerging technologies, methodologies, and industry trends in AI/ML

Bonus: Knowledge of MLOps, FastAPI, Docker, CI/CD, and cloud platforms such as Azure or AWS

• Cutting-Edge Projects: Opportunity to work with industry-defining technologies in terms of applied research and pushing functional boundaries
• Vibrant Work Environment: We have technical experts from 25 nationalities as part of our team and disruptive ideas are a daily occurrence
• Work-Life Balance: flexible work hours and remote work options
• Competitive Pay: salary that aligns with industry standards
• Generous Vacation Time: 25 days of annual paid vacation
• Health and Wellness Benefits: Dedicated yearly health and wellness allocation