Robotics & Machine Learning Engineer

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Robotics & Machine Learning Engineer, london (city of london)

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Client:

Opus Recruitment Solutions
Location:

london (city of london), United Kingdom
Job Category:

Other
-
EU work permit required:

Yes
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Job Views:

4
Posted:

26.06.2025
Expiry Date:

10.08.2025
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Job Description:

? Machine Learning Engineer – Robotic Manipulation | Cutting-Edge Space Tech | Equity Opportunity ?
Location:

Hybrid (UK-based)
Join a stealth-mode innovator at the forefront of autonomous robotics, building next-gen systems that operate in the most extreme environments—space. This is your chance to shape the future of orbital infrastructure and space domain defence.
We're on the hunt for a

Machine Learning Engineer

with a passion for robotic manipulation. You’ll be the mastermind behind intelligent grasping systems—designing, training, and deploying ML models that enable robots to interact with unknown objects in unpredictable environments.
This isn’t just another ML role. It’s a chance to take your work from simulation to spaceflight. ??️
? What You’ll Be Doing
Design and train models for real-time grasp prediction and evaluation.
Build high-fidelity simulators to train and test your policies.
Deploy models to edge compute platforms for real-time inference.
Collaborate across robotics, vision, hardware, and software teams to bring your models to life.
Own performance benchmarking and real-world validation.
? What You Bring
5+ years in ML, Robotics, or Reinforcement Learning (or equivalent hands-on experience).
Deep understanding of robot manipulation—both classical and ML-based approaches.
Proficiency in Python & C++, and experience with ML frameworks like PyTorch or TensorFlow.
Strong grasp of real-world robotic constraints and embedded systems.
Excellent communication and a collaborative mindset.
? Bonus Points For
Experience deploying robotic systems in real-world environments.
Knowledge of 6-DOF pose estimation, tactile feedback, or real-time control.
Comfort with Linux, Git, Docker, and real-time systems.

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