Edge AI Engineer

Jobbeskrivning Sigma Connectivity’s Edge AI initiatives span multiple domains—computer vision, audio intelligence, sensor fusion, and embedded ML—delivering low‑latency, privacy‑preserving intelligence directly on devices across diverse hardware platforms. Projects routinely involve developing and optimizing ML models for tasks such as gesture recognition, defect detection, object tracking, and contextual human‑machine interaction, deployed on edge hardware including Qualcomm, NVIDIA, NXP, and other MCU‑class systems. Work includes quantization, DSP/NPU acceleration, real‑time analytics, and combined cloud–edge pipelines that enhance precision while keeping compute close to the data source. We are looking for a skilled ML Engineer to join our growing team and contribute to the development of advanced edge AI solutions. Your work will include - 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. We are looking for - 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 We Provide - 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 whether it is a groundbreaking mesh technology, a radical approach to manage power and performance on edge devices, or creative solutions to enhance model efficiency. Work-Life Balance: We understand the importance of balancing work and personal life. Our flexible work hours and remote work options help you maintain this balance. Competitive Pay: We offer a salary that aligns with industry standards, ensuring you are fairly compensated for your skills and experience. Generous Vacation Time: Enjoy a healthy work-life balance with 25 days of annual paid vacation. We believe time off is crucial for your well-being and productivity. Health and Wellness Benefits: Dedicated yearly health and wellness allocation.