Robotic Manipulation Engineer

About the Role

Are you excited by the challenge of teaching robots how to understand and manipulate the physical world? Do you want to build real systems that use machine learning and perception to grasp and interact in unstructured and unknown environments? Do you thrive in fast-paced, multidisciplinary teams solving hard problems?

If so, you’ll fit right in at Lodestar Space! We’re a team of roboticists, engineers, and dreamers, committed to building the future of space infrastructure, and space domain defence. Our robotic systems are designed to perform autonomous manipulation in the harshest and most complex environments imaginable.

We’re looking for a Machine Learning Robotic Manipulation Engineer to lead development of the core ML-based grasping stack for our robotic capture system. In this role, you’ll research, design, and implement models and pipelines that enable perception-driven grasp planning—bridging the gap between computer vision, motion planning, and real-world physical interaction with unknown objects.

You’ll work closely with Machine Vision, Robotics, Hardware, Systems, and Software teams, to take your models from the lab to orbit—from simulation to flight. If you're passionate about robotics and want to see your work in action, this is the role for you.

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What You’ll Do

• Lead development of machine learning systems for real world grasping and manipulation of unknown objects in space.
• Design and train models for arbitrary grasp candidate prediction and real-time grasp quality evaluation.
• Build high fidelity physics simulators to train and evaluate grasp policies.
• Deploy and fine-tune grasp models to achieve real-time inference on our edge compute platform.
• Collaborate with robotics, perception, hardware, software, and systems teams to ensure seamless integration.
• Own performance benchmarking, real-world validation, and iteration for grasp reliability.

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What We’re Looking For

We're seeking a builder—someone who’s both research-minded and implementation-driven. You should be eager to take ownership, collaborate deeply, and see your ideas go from prototype to mission-ready.

Qualifications

• 5+ years of experience in Machine Learning, Robotics, Reinforcement learning, or a related field (or equivalent practical experience).
• Lead the end-to-end grasping pipeline.
• Understand both traditional and machine learning approaches to robot manipulation, and the tradeoffs between various techniques.
• Bachelor’s or Master’s in Computer Science, Mathematics, Electrical Engineering, related field or demonstrated an equivalent level of knowledge.
• Deep understanding of the fundamentals of machine learning.
• Experience with  machine learning frameworks (e.g. PyTorch, TensorFlow).
• Hands-on proficiency in C++ and Python.
• Familiarity with robotic simulation environments (e.g. NVIDIA Omniverse, MuJoCo, PyBullet).
• Solid grasp of real-world constraints in robotic perception and manipulation.
• Strong communication and collaboration skills.

Preferred Qualifications

• Experience implementing, testing, and deploying robot manipulation solutions in C++ and/or Python on real robots.
• Familiarity with real-time perception and control on embedded systems.
• Prior work on vision-based grasping systems, 6-DOF pose estimation, or tactile feedback loops.
• Comfortable working on Linux-based platforms.
• Proficiency in using version control tools such as Git or SVN.
• Familiarity with containerisation technologies such as Docker.
• Experience with real-time systems.

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Important Information

For security reasons background checks will be undertaken prior to any employment offers being made to an applicant. These checks will include nationality checks as it is a requirement of this position that you be eligible to access equipment and data regulated by the United States' International Traffic in Arms Regulations. 

Under these Regulations, you may be ineligible for this role if you do not hold citizenship of the United Kingdom, Australia, Japan, New Zealand, Switzerland, the European Union or a country that is part of NATO, or if you hold ineligible dual citizenship or nationality.  For more information on these Regulations, click here ITAR Regulations.

Benefits

• Competitive Salary (based on experience)
• Equity pool options
• Vibrant, open-plan office in London
• 28 Days Annual Leave
• Private Medical Insurance
• Be part of a scrappy, dynamic, multidisciplinary, collaborative crew 🏴‍☠️

At Lodestar Space, we value people with unique experiences, and skill sets. If you’re interested in this role and want to make an impact on a global scale, please apply!