Staff AI / ML Robotics Engineer - Environmental Perception

Analog Devices, Inc. is a global semiconductor leader that bridges the physical and digital worlds to enable breakthroughs at the Intelligent Edge. ADI combines analog, digital, and software technologies into solutions that help drive advancements in digitized factories, mobility, and digital healthcare, combat climate change, and reliably connect humans and the world.

Staff Engineer – AI for Perception, SLAM, and Sensor Fusion

Location: Edinburgh, Scotland

Team: Edge AI Group, Analog Devices Inc. (ADI)

Analog Devices’ Edge AI team is on a mission to redefine how machines perceive and interact with the world. We’re building real-time, intelligent systems that combine world-class sensor technology with cutting-edge AI — at the Edge, where milliseconds matter.

We are looking for a Staff AI/ML Engineer with a strong background in robot perception, SLAM, and sensor fusion to help us build systems that localize, map, and understand complex environments. Whether it’s a mobile robot navigating a warehouse, or an intelligent sensor inferring structure from sparse data — your algorithms will enable precise, real-time environmental awareness.

You’ll be a core contributor to the development of robust and efficient AI-based perception systems, working alongside experts in hardware, embedded systems, and AI software. This is a hands-on role that blends applied research with production-grade engineering.

Responsibilities

• Design, prototype, and deploy algorithms for SLAM, visual odometry, and multi-sensor fusion (e.g., camera, IMU, LiDAR, encoders) in robotics and edge computing applications.
• Develop AI-driven methods for mapping, pose estimation, localization, and semantic perception, with an emphasis on performance and generalization.
• Train and evaluate deep learning models for spatial understanding, integrating with classical perception pipelines when needed.
• Work with real-world and simulated sensor data to test and refine models; contribute to internal datasets and benchmarking tools.
• Collaborate with embedded, systems, and software teams to bring perception solutions to production on resource-constrained edge platforms.
• Participate in project planning, code reviews, and architectural discussions; take ownership of technical areas and deliver high-quality, reliable implementations.
• Stay current with trends in AI for robotics (e.g., transformer-based perception, self-supervised learning, foundation models), and help integrate relevant advancements into our workflows.

Qualifications

• 6+ years of experience in AI, robotics, or computer vision, including 4+ years focused on SLAM, sensor fusion, or perception systems.
• Bachelor’s degree in a relevant field (e.g., Robotics, Computer Science, Electrical Engineering); M.S. or Ph.D. preferred.
• Strong understanding of 3D geometry, motion estimation, sensor fusion, and real-time system design.
• Hands-on experience building and deploying SLAM or VIO systems (e.g., ORB-SLAM, RTAB-Map, DSO, OpenVINS, Cartographer).
• Proficient in Python and C++, with practical experience using PyTorch, TensorFlow, or ROS.
• Comfortable working with real-world sensor data (e.g., stereo cameras, LiDAR, IMU) and simulation tools like Gazebo, Isaac Sim, or Unreal.
• Experience with DevOps/MLOps tools: Docker, CI/CD pipelines, cloud platforms (Azure, AWS), version control (Git).
• Skilled at communicating technical insights, collaborating with multi-disciplinary teams, and contributing to shared architectural decisions.

Bonus Experience

• Experience integrating perception models with control loops, path planning, or robot operating systems (ROS2).
• Knowledge of self-supervised or foundation model-based perception techniques.
• Familiarity with industrial robotics, AMRs, or autonomous systems in structured environments.
• Contributions to open-source robotics or AI frameworks.

Why Join Us?

Join ADI’s Edge AI team to help create truly intelligent edge systems — where sensing, learning, and acting happen in real time. You’ll work in a fast-paced, collaborative environment, solving hard problems with people who care about impact, reliability, and real-world performance.