Manipulation Capabilities Engineer

Thehumanoid; Greater London; On-site; GBP 70,000 - 90,000; Full time

Benefits offered by this job

23 days of annual leave

Fully funded private healthcare

Free daily breakfast

Equity options

Pension scheme with 8% total contribution

Job summary

Thehumanoid is hiring a Manipulation Capabilities Engineer in London. This role involves developing strategies for our robots to manipulate their environment, focusing on applied deep learning and real hardware experience. Candidates should have at least 3 years of experience in robotics and familiarity with neural network post-training. The position includes a collaborative work environment with top-tier engineers and offers significant benefits including equity, private healthcare, and generous leave policies.

Qualifications

• Minimum of 3 years working on robots with shipped artifacts.
• Proficient in neural network post-training and debugging numerics.
• Good understanding of teleoperations and low-level controls.

Responsibilities

• Post-train manipulation policies and own the deployment process.
• Develop data preprocessing strategies.
• Collaborate with simulation teams for RL training.

Skills

Experience with robots (industry or research)

Neural network post-training

Deep learning infrastructure

Modern software engineering practices

Documentation and communication skills

Tools

PyTorch

JAX

Job description

Here at Humanoid, we believe in a future where robots amplify human potential. That’s why we’ve set out on a mission to build the world’s most capable, commercially-scalable, and safe humanoid robots. We’re bringing that mission to life with HMND‑01 Alpha - our rapidly developed humanoid platform now running in real industrial pilots - and we’re growing the team to take it even further.

About The Role

We're hiring a strong Manipulation Capabilities Engineer to join our team based in London.

In this role, you will work on teaching our robots to manipulate the world around them.

This is a role at the intersection of applied deep learning and robotics, and to be set up for success you need both experience of working with real robot hardware (e.g. identifying issues in control or teleop), and applied deep learning (you don’t have to be an expert on cutting edge neural network techniques, but you should be perfectly capable of curating data, fine-tuning a policy on that data and hypothesising potential mitigations when something doesn’t work).

What You’ll Do

• Post-train manipulation policies via behaviour cloning and RL; own the full loop from data to deployment.
• Come up with data preprocessing strategies to improve the quality of collected data.
• Work with the simulation team to set up RL training using digital twin, and then iterate on reward and simulation quality to ensure successful transfer to the real world.
• Partner with the data collection organization to drive data collection activities for a specific capability: specify what good data looks like, ensure diversity and coverage, and iterate on instructions.
• Expand observation and action spaces with new components required to support novel capabilities, and work with the Teleoperations team to expose these components to robot operators.
• Partner with Teleoperations and Controls teams to improve motion smoothness and teleoperation experience.
• Interface with hardware design team to ensure that manipulation team findings regarding the current generation of hardware are reflected in future designs.

What We're Looking For

• 3+ years working on robots (industry or research) with shipped artifacts to show for it. A good understanding of modern teleoperation and low-level control stack.
• Experience with neural network post-training.
• Familiarity with deep learning infrastructure: streaming datasets, checkpointing & state management, distributed training, PyTorch or JAX. Ability to profile & debug numerics and write maintainable research code.
• Good familiarity with modern software engineering practices.
• Ability to document experiments clearly and communicate trade‑offs crisply.

Nice to have:

• Experience training VLA models for manipulation (autoregressive, diffusion or flow-matching based). Familiarity with OpenVLA, Physical Intelligence (π) models, or similar open VLA frameworks.
• Experience applying RL to robotics problems.
• Publications at top-tier robotics or deep learning conferences or equivalent open‑source contributions.

What We Offer

• Meaningful time off to rest and recharge: 23 days of annual leave (accrued), 15 days of paid sick leave, and paid company holidays.
• Fully funded private healthcare for UK employees, with broad provider access, virtual and in‑person care, and strong mental health and serious illness support.
• Equity included–we believe builders should share in what they build.
• Pension scheme with a total 8% contribution (5% employee, 3% employer) on full earnings.
• Free daily breakfast, catered lunch, and snacks in‑office.
• Collaboration with top‑tier engineers, researchers, and product experts in AI and robotics.
• Freedom to influence the product and own key initiatives.