Edge AI Engineer (Embedded ML)

TL;DR

Edge AI Engineer (Embedded ML): Designing and optimizing ML models for computer vision and sensor fusion on edge hardware with an accent on quantization and NPU acceleration. Focus on developing low-latency, privacy-preserving intelligence for devices using Qualcomm, NVIDIA, and NXP platforms.

Location: Lund, Sweden (remote work options available)

Company

Global leader in providing custom software and hardware solutions, specializing in connected products for consumer electronics and IoT devices.

What you will do

• Design, train, and validate ML models for computer vision, sensor fusion, signal processing, and predictive analytics.
• Develop and optimize on-device inference pipelines, including quantization, power/performance tuning, and DSP/NPU acceleration.
• Build data ingestion and feature-engineering pipelines for both edge and hybrid deployments.
• Collaborate with architects, embedded developers, and customers to integrate ML functionality into real products.
• Monitor, test, and optimize the performance of deployed models to ensure accuracy and scalability.
• Conduct prototyping and PoCs, contributing to technical presentations and customer dialogues.

Requirements

• Strong hands-on experience in Python, ML frameworks (PyTorch or TensorFlow), and CV libraries (OpenCV, scikit-learn).
• Ability to build and deploy ML models for Edge/Embedded platforms, preferably Qualcomm, Nordic, or NXP SoCs.
• Familiarity with quantization, model compression, benchmarking, and inference profiling on constrained hardware.
• 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 computer vision, time-series, or sensor-data ML.

Nice to have

• Knowledge of MLOps, FastAPI, Docker, and CI/CD.
• Experience with cloud platforms such as Azure or AWS.

Culture & Benefits

• Opportunity to work on industry-defining projects in applied research.
• Vibrant, international environment with experts from 25 different nationalities.
• Flexible work hours and remote work options for better work-life balance.
• Competitive pay aligned with industry standards.
• 25 days of annual paid vacation and a dedicated yearly health and wellness allocation.