Who we are
With its A.I.-powered robotic technology platform, Symbotic is changing the way consumer goods move through the supply chain. Intelligent software orchestrates advanced robots in a high-density, end-to-end system - reinventing warehouse automation for increased efficiency, speed and flexibility.
What we need
We're seeking a SLAM expert with several years of experience to join the Perception team at the Principal Engineer level. As a SLAM Expert, you will play a technical leadership role in developing and implementing state-of-the-art SLAM algorithms and systems to advance our cutting-edge fulfillment technology. We are looking for people who thrive in a creative, collaborative, and agile development environment.
What we do
We are a talented team of roboticists working on the heart of Symbotic's automation solution - Symbot, the mobile robot. We are responsible for delivering solutions for the storage and retrieval use cases performed in a fully autonomous structure operating 100s of Symbots at customer sites.
What you'll need

• Develop, optimize, and implement SLAM algorithms and systems for real-time applications.
• Conduct research and stay up-to-date with the latest advancements in SLAM and related fields.
• Design and execute experiments to evaluate the performance and robustness of SLAM algorithms and systems.
• Collaborate with cross-functional teams, including software engineers, computer vision experts, and robotics engineers, to integrate SLAM solutions into various projects.
• Provide technical guidance and support to team members working on SLAM-related projects.
• Identify and analyze challenges in SLAM implementation and propose innovative solutions.
• Contribute to the development of tools and frameworks to streamline the SLAM development process.
• Document and communicate research findings, algorithms, and technical specifications effectively.

What you will do

• A Master's or Ph.D. degree in Computer Science, Robotics, Electrical Engineering, or a related field.
• 8-12 years' of demonstrated experience in SLAM research and development, with a strong publication record in relevant conferences or journals.
• Expertise in various SLAM techniques, such as visual SLAM, LiDAR SLAM, visual-inertial SLAM, graph-based SLAM, Kalman filtering, bundle adjustment, structure from motion, etc.
• Proficiency in programming languages commonly used in SLAM, such as C , Python, and MATLAB.
• Solid understanding of computer vision, sensor fusion, probabilistic robotics, and optimization algorithms.
• Experience with popular SLAM libraries and frameworks, such as ROS, OpenCV, PCL, GTSAM, and g2o.
• Strong mathematical and analytical skills, with the ability to apply advanced mathematical concepts to solve SLAM challenges.
• Strong communication and teamwork skills to collaborate effectively with interdisciplinary teams.
• Prior experience working with autonomous systems and robotics.

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About Symbotic
Symbotic is an automation technology leader reimagining the supply chain with its end-to-end, AI-powered robotic and software platform. Symbotic reinvents the warehouse as a strategic asset for the world's largest retail, wholesale, and food & beverage companies. Applying next-gen technology, high-density storage and machine learning to solve today's complex distribution challenges, Symbotic enables companies to move goods with unmatched speed, agility, accuracy and efficiency. As the backbone of commerce the Symbotic platform transforms the flow of goods and the economics of supply chain for its customers. For more information, visit www.symbotic.com .
We are a community of innovators, collaborators and pioneers who embrace our differences, because we know unique perspectives make us stronger and smarter. Every perspective matters. We depend on the collective voices of our employees, customers and community to help guide us as we build a better place to work - for you and the world. That's why we're proud to be an equal opportunity employer.
We do not discriminate based on race, color, ethnicity, ancestry, religion, sex, national origin, sexual orientation, age, citizenship status, marital status, disability, gender identity, gender expression, veteran status, or genetic information.