Principal AI/ ML Robotics Engineer - Environmental Perception

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Principal AI/ ML Robotics Engineer - Environmental Perception page is loaded## Principal AI/ ML Robotics Engineer - Environmental Perceptionlocations: United Kingdom, Edinburgh, SC, Freerposted on: Posted Todayjob requisition id: R255366**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. Learn more at and on and .**Principal Engineer – AI for Visual Perception, SLAM, and Sensor Fusion****Location:** Edinburgh, Scotland**Team:** Edge AI Group, Analog Devices Inc. (ADI)Analog Devices’ Edge AI team is building the next generation of intelligent sensing systems that reshape how machines perceive and interact with the physical world. From deeply embedded algorithms to scalable AI applications, we work across the full stack to fuse advanced hardware with real-time intelligence. Our mission: bring AI to the Edge — where decisions meet the real world.We are looking for a Principal Engineer with deep domain expertise in visual odometry, sensor fusion, SLAM, and AI-based perception to lead the development of real-world localization and mapping solutions. You will work at the intersection of embedded sensing, robotics, and machine learning, helping create systems that can understand, navigate, and adapt to their environments autonomously — in factories, warehouses, vehicles, and beyond.You will join a high-impact team developing foundational components for ADI’s next wave of perception-enabled solutions. This is a hands-on leadership role for someone who thrives on solving open-ended challenges, defining technical roadmaps, and mentoring other engineers.**Responsibilities*** Lead the design and deployment of **SLAM, VIO, and multi-sensor fusion systems** that enable robust, real-time mapping and localization across diverse environments.* Drive **algorithm development and evaluation** for perception tasks, including **pose estimation, depth reconstruction, loop closure, map optimization**, and semantic understanding.* Architect AI pipelines that combine **classical and learned methods** (e.g., CNNs, transformers, foundation models) for environmental understanding at the edge.* Develop real-world and simulation-based datasets for benchmarking and validation; guide sensor selection and system integration.* Collaborate cross-functionally with embedded, hardware, and systems engineers to bring scalable solutions from research to production.* Stay current with the state of the art in robotics, SLAM, Edge AI, and self-supervised learning — and guide the team in adopting innovative technologies.* Contribute to the broader AI platform architecture, CI/CD pipelines, and MLOps practices.**Qualifications*** **10+ years** of experience in robotics, computer vision, or AI, including **5+ years in SLAM, VO, or sensor fusion**; with **3+ years in a technical leadership role**.* M.S. or Ph.D. in Robotics, Computer Science, Electrical Engineering, or related field.* Demonstrated expertise in at least one of the following: + **Visual-inertial odometry (VIO)** + **Multi-sensor fusion (camera, LiDAR, IMU, encoders)** + **3D SLAM and mapping in dynamic environments** + **AI-based perception models for real-time localization*** Proven track record of deploying perception algorithms in real-world systems (e.g., autonomous robots, drones, AR/VR, self-driving platforms).* Strong programming skills in **Python and C++**, with experience in frameworks like **PyTorch**, **ROS**, **g2o**, or **Ceres**.* Comfortable working with **real-time systems**, embedded platforms, or simulators such as Gazebo, Isaac Sim, or Unreal Engine.* Familiar with **MLOps** and software best practices: CI/CD, containerization (Docker), orchestration (Kubernetes), etc.* Excellent communicator and collaborator — capable of leading multi-disciplinary teams and influencing stakeholders across hardware, software, and business domains.**Bonus Experience (Nice to Have)*** Experience with **self-supervised learning**, **foundation models for robotics**, or **transformer-based perception architectures**.* Familiarity with industrial domains: **factory automation, AMRs, predictive maintenance**, etc.* Prior contributions to open-source projects (e.g., OpenVINS, ORB-SLAM3, DROID-SLAM, RTAB-Map, Cartographer).* Understanding of **sensor design**, **signal processing**, or **embedded AI hardware platforms**.Join us in shaping the future of edge intelligence — where your work bridges the gap between sensing and understanding, and where you’ll help machines not just gather data, but act meaningfully in the world.### ### #LI-BF1### *For positions requiring access to technical data, Analog Devices, Inc. may have to obtain export licensing approval from the U.S. Department of Commerce - Bureau of Industry and Security and/or the U.S. Department of State - Directorate of Defense Trade Controls. As such, applicants for this position – except US Citizens, US Permanent Residents, and protected individuals as defined by 8 U.S.C. 1324b(a)(3) – may have to go through an export licensing review process.**Analog Devices is an equal opportunity employer. We foster a culture where everyone has an opportunity to succeed regardless of their race, color, religion, age, ancestry, national origin, social or ethnic origin, sex, sexual orientation, gender, gender identity, gender expression, marital status, pregnancy, parental status, disability, medical condition, genetic information, military or veteran status, union membership, and political affiliation, or any other legally protected group.*Job Req Type: ExperiencedRequired Travel: Yes, 10% of the timeShift Type: 1st Shift/Days #J-18808-Ljbffr
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