Embedded AI/ML Engineer

Design edge-AI algorithms and embedded software for intelligent transportation and urban mobility systems!

Embedded AI/ML Engineer – Smart Mobility Solutions (Remote – Portugal / Lisbon-based)

We are seeking a passionate and skilled Embedded AI/ML Engineer to work remotely from Portugal, contributing to the development of intelligent, edge-based solutions for smart mobility systems for one of our clients. In this role, you’ll design and implement AI algorithms optimized for embedded platforms used in applications such as connected vehicles, traffic prediction, and autonomous transport. Join a forward-looking team dedicated to reshaping how mobility and urban infrastructure interact.

Core Responsibilities:

• Design and implement AI/ML models for execution on resource-constrained embedded systems
• Optimize neural networks for performance and power efficiency on devices like NVIDIA Jetson, ARM Cortex, or similar platforms
• Collaborate with software and hardware teams to deploy scalable and reliable edge-AI solutions
• Integrate sensor data (vision, GPS, LIDAR) and apply ML techniques to real-world mobility challenges
• Conduct model training, quantization, pruning, and inference benchmarking
• Ensure compliance with software quality and cybersecurity standards in embedded deployments

Core Skills Required:

• Strong proficiency in Python and C/C++
• Hands-on experience with TensorFlow Lite, ONNX, PyTorch Mobile, or similar frameworks
• Familiarity with edge computing and embedded system constraints (e.g., memory, latency, power)
• Knowledge of embedded Linux or RTOS environments
• Experience in deploying real-time ML models on devices like Jetson Nano/Xavier, Raspberry Pi, or custom boards
• Understanding of AI model optimization techniques (e.g., quantization, compression)

Preferred / Additional Skills:

• Experience with computer vision and sensor fusion for mobility-related applications
• Knowledge of communication protocols (e.g., CAN, MQTT, V2X)
• Familiarity with data privacy, GDPR, and cybersecurity principles in AI systems
• Background in autonomous vehicles, urban infrastructure, or transportation tech
• Degree in Electrical Engineering, Computer Science, AI, or similar