At a Glance
- Tasks: Design and deploy cutting-edge AI algorithms for robotics and environmental perception.
- Company: Join Analog Devices, a leader in semiconductor technology and innovation.
- Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
- Why this job: Make a real impact in AI and robotics while working with top experts in the field.
- Qualifications: 6+ years in AI/robotics, strong SLAM and sensor fusion skills required.
- Other info: Collaborative environment focused on solving complex real-world problems.
The predicted salary is between 48000 - 84000 £ per year.
About Analog Devices
Analog Devices, Inc. (NASDAQ: ) 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. With revenue of more than $9 billion in FY24 and approximately 24,000 people globally, ADI ensures today's innovators stay Ahead of What's Possible.
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.
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.
Staff AI / ML Robotics Engineer - Environmental Perception in Edinburgh employer: Analog Devices, Inc.
Contact Detail:
Analog Devices, Inc. Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Staff AI / ML Robotics Engineer - Environmental Perception in Edinburgh
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with potential colleagues on LinkedIn. You never know who might have the inside scoop on job openings or can put in a good word for you.
✨Tip Number 2
Prepare for interviews by practising common questions related to AI, robotics, and perception systems. We recommend doing mock interviews with friends or using online platforms to get comfortable discussing your experience and skills.
✨Tip Number 3
Showcase your projects! Whether it's a GitHub repository or a personal website, having a portfolio of your work can really set you apart. Make sure to highlight any relevant SLAM or sensor fusion projects you've worked on.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you're genuinely interested in joining our team at Analog Devices.
We think you need these skills to ace Staff AI / ML Robotics Engineer - Environmental Perception in Edinburgh
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the role of Staff AI/ML Robotics Engineer. Highlight your experience with SLAM, sensor fusion, and any relevant projects that showcase your skills in robotics and AI.
Craft a Compelling Cover Letter: Your cover letter should tell us why you're passionate about environmental perception and how your background makes you a perfect fit for our team. Be sure to mention specific technologies or methodologies you've worked with.
Showcase Your Projects: Include links to any relevant projects or GitHub repositories that demonstrate your hands-on experience with AI and robotics. We love seeing practical applications of your skills!
Apply Through Our Website: Don’t forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it shows you’re serious about joining our team.
How to prepare for a job interview at Analog Devices, Inc.
✨Know Your Algorithms
Make sure you brush up on your knowledge of SLAM, visual odometry, and sensor fusion algorithms. Be ready to discuss how you've applied these in real-world scenarios, as well as any challenges you faced and how you overcame them.
✨Showcase Your Hands-On Experience
Prepare to talk about specific projects where you've built and deployed SLAM or VIO systems. Highlight your experience with tools like ORB-SLAM or RTAB-Map, and be ready to explain the impact of your work on the overall project.
✨Familiarise Yourself with the Tech Stack
Since the role requires proficiency in Python and C++, make sure you're comfortable discussing your experience with these languages. Also, be prepared to talk about your use of frameworks like PyTorch or TensorFlow, and how you've integrated them into your projects.
✨Stay Current with Trends
Research the latest advancements in AI for robotics, such as transformer-based perception and self-supervised learning. Being able to discuss these trends will show your passion for the field and your commitment to staying ahead of the curve.