Lead Research Engineer (SLAM/State estimation)

Are you a skilled engineer with a passion for Computer Vision, SLAM and state estimation? Join our innovative team as a Lead Research Engineer and help shape the future of autonomous systems.

• A chance to work in a fascinating industry. Other companies say they’re cutting edge; we’re literally at the forefront of spatial intelligence.
• Packed with benefits and perks, including hybrid working, enhanced employer pension contributions, unlimited external private coaching, frequent social events, cash to spend on your home setup, and more.
• Play a pivotal role in deploying autonomous solutions for some of the biggest names in warehousing and intralogistics worldwide.

The top line

Visual SLAM has evolved from research into real-world applications, but this is just the beginning. SLAM is quickly transforming into general Spatial AI, enabling intelligent devices to understand and interact with their geometric and semantic surroundings.

Slamcore is at the heart of this revolution, delivering advanced Spatial AI solutions to clients in robotics, intralogistics, and warehouse automation. This is your opportunity to join a fast-growing tech company in a key position.

We're looking for someone with a strong background in mathematics or computer science, experienced in developing and deploying state estimation algorithms on embedded platforms in industrial environments. If you're passionate about SLAM, Computer Vision, and state estimation, and are excited to join a world-class team, we want to hear from you!

The good stuff

• Slamcore is a hybrid-first company, however, ideally you’ll live within commuting distance of our London HQ so you can visit the office regularly
• 25 days’ holiday a year plus 8 UK public holidays – plus bonus time off between Christmas and New Year.
• Enhanced employer pension contributions 
• Private health insurance 
• Meaningful equity in a fast-growing business
• Flexible working arrangements
• Generous professional and personal development budget, including unlimited private coaching sessions with More Happi.
• Frequent team social events, free weekly team lunches, snacks and a fully stocked drinks fridge at our Borough HQ.
• Your own company card for getting equipment, training, books, snacks, and coffee
• £500 to spend on your work-from-home setup
• Enhanced parental leave

The day-to-day

• Design and develop state-of-the-art SLAM and perception algorithms for high-performance localisation, mapping, and scene understanding
• Create high-quality Spatial AI systems that enable real-world applications
• Collaborate closely with Product teams to turn innovations into customer solutions for robotics and automation
• Work alongside SLAM and software engineering experts to innovate in applied Spatial AI

The must-haves

• Strong background in geometric computer vision, state estimation, or SLAM
• Expertise in optimisation, numerical linear algebra, and sensor fusion
• Industrial experience in deploying SLAM solutions
• Proficiency in C++

The nice-to-haves

• PhD in computer vision or robotics
• Experience with machine learning techniques for geometric and semantic estimation
• GPU programming skills (CUDA, OpenCL, Vulkan, Metal)
• Experience with embedded software development

All about us

We’re a London-based startup founded by visual SLAM algorithm pioneers. Having raised over $30M in funding from top investors around the world, we’re developing breakthrough spatial intelligence technologies for the next generation of intralogistics solutions.

Next steps

There’s loads more info about us on our website. We’d suggest 'About' and 'Meet the team' as your first two stops to learn more about the industry, and what it’s like to work here.

Sound good? If you are interested, just hit Apply Now to get the ball rolling.

We are an equal opportunity employer and value diversity at our company. We do not discriminate on the grounds of gender, sexual orientation, marital or civil partner status, pregnancy or maternity, gender reassignment, race, colour, nationality, ethnic or national origin, religion or belief, disability or age. #LI-DNI