---
title: 'Robotics Learning Engineer at Humanoid'
canonical: 'https://feeny.ai/job/robotics-learning-engineer-humanoid-london-7fgkkmdqae2x'
type: 'job'
last_seen: '2026-09-10'
---

# Robotics Learning Engineer at Humanoid

- **Company:** [Humanoid](https://feeny.ai/companies/humanoid)
- **Location:** London, United Kingdom
- **Employment:** full-time
- **Work type:** onsite
- **Posted:** 2026-04-17
- **Last confirmed live:** 2026-09-10
- **Apply:** https://jobs.ashbyhq.com/humanoid/0374a4ab-3cfe-4bd8-aef7-bc1edc87621a/application

**Skills:** Deep Learning, PyTorch, JAX, Reinforcement Learning, Behavior Cloning, Neural Network Post-training, Distributed Training, State Management, Numerical Profiling, Software Engineering, Robot Hardware, Teleoperation, Low-level Control, Visual Language Models (VLA), OpenVLA, Physical Intelligence (π) Models, Autoregressive Models, Diffusion Models, Flow-matching Models, Flow-based Models

> The Manipulation Capabilities Engineer teaches robots to manipulate the world by combining applied deep learning with real robot hardware. Responsibilities include post-training policies via behavior cloning and reinforcement learning, data preprocessing, and sim-to-real transfer. The role involves collaborating wit...

## 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 Robotics Learning Engineer to join our Manipulation 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

- Competitive equity: stock options with meaningful upside as we scale.
- 30+ paid days off, including 23 days of annual leave, all UK bank holidays, and additional company closure days (including Christmas–New Year shutdown).
- Private healthcare, including virtual and in-person care.
- Pension scheme with 8% total contribution (5% employee, 3% employer) on full earnings.
- Free daily breakfast, catered lunch, and snacks in-office.
- Work at the frontier - collaborate daily with world-class engineers, researchers, and product experts building the next generation of AI and humanoid robotics.
- Real ownership - direct access to founding leadership, meaningful input on product direction, and the ability to drive key initiatives from day one.

## About Humanoid

## Company Overview
- **One-liner**: Humanoid builds commercially scalable, safe, and reliable humanoid robots designed to automate labor-intensive industrial tasks across warehousing, logistics, manufacturing, and retail.
- **Entity Type**: Private (Seed stage)
- **Headquarters**: London, United Kingdom (HQ) with offices in Cambridge, MA, USA; Burnaby, BC, Canada; and additional presence in Germany, Georgia, and the UAE.
- **Founded**: 2024
- **Founders**: Artem Sokolov (CEO & Founder)

## Core Business
- **Primary industry/industries**: Robotics Engineering, Humanoid Robotics, Industrial Automation, Artificial Intelligence
- **Target customers**: B2B / Enterprise — industrial sectors including retail, e-commerce, third-party logistics (3PL), manufacturing, and automotive.
- **Mission or purpose statement**: “Empowering humanity by building the most reliable, safe, and helpful humanoid robots.” The company aims to free people from repetitive, dangerous, and tedious work, allowing them to engage in more creative and meaningful activities.

## Products & Services
- **HMND 01 Alpha Wheeled**: A robust industrial-grade wheeled humanoid robot designed for material handling, pick-and-place, and visual inspection in warehouses and factories. Prioritizes reliability, low total cost of ownership (TCO), and minimal maintenance.
- **HMND 01 Alpha Bipedal**: A bipedal humanoid robot for more complex environments requiring advanced locomotion, navigation of confined spaces, and higher dexterity. Features human-level manipulation speeds and walking speeds up to 1.5 m/s.
- **KinetIQ**: An AI framework for orchestrating fleets of humanoid robots across both wheeled and bipedal platforms, enabling centralized control and task optimization.
- **Modular Garments**: Exchangeable protective “garments” that allow HMND 01 robots to adapt to different use cases and environments, minimizing contamination and collision damage while enabling functional customization.

## Market Standing
- **Valuation/Market Cap**: Not disclosed.
- **Key Metric**: Total funding of **$50 million** (Seed round closed October 2025, with 1 lead investor).
- **Notable Investors/Partners**: Strategic partners include leading global companies in AI, cloud computing, and research. Specific partner names are not publicly listed on the website, but the company highlights collaboration with commercial partners to scale deployment.
- **Growth Signals**:
  - Headcount grew **139.2% YoY** to ~182 employees (as of mid-2026), with 65 active job postings.
  - Opened offices in London, Boston, and Vancouver within its first year.
  - Team includes talent recruited from major robotics and AI firms: Sanctuary AI, Boston Dynamics, Dyson, Arrival, Ocado Technology, 1X, Wayve, Apptronik, and Brain Corp.
  - Focus on initial target sectors representing a combined $12 trillion in annual payroll and 250 million workers.

## Competitive Advantages
- **Human-centric design**: The world is already designed for humans, so humanoids can seamlessly integrate into existing environments without costly redesign.
- **Modularity**: HMND 01’s hardware/software modularity enables multi-task performance and easy repurposing, reducing the need for specialized robots.
- **Reliability & low TCO**: Prioritizing hardware and software stability over raw performance to deliver industrial-grade robustness suitable for mass commercialization.
- **KinetIQ fleet orchestration AI**: Proprietary framework for managing mixed fleets of wheeled and bipedal robots, differentiating from competitors focused on single-form-factor robots.
- **Experienced leadership**: CEO Artem Sokolov previously scaled a family manufacturing business into a billion-dollar enterprise (EY Entrepreneur of the Year 2021). The CTO, Jarad Cannon, has extensive experience translating research into deployment-ready robotics systems.

## Strategic Focus
- **Near-term (2027)**: Deploy robots for physical tasks in manufacturing, warehousing, logistics, and retail — tackling repetitive, dangerous, and tedious manual work.
- **Medium-term (2029)**: Expand into the service sector, targeting the 70-80% of the global economy that will be services, with a focus on assisting an aging population (1.4B people over 60).
- **Long-term (2031+)**: Enter households as assistants and companions, potentially revolutionizing everyday life across 3.5 billion homes.
- **Core strategy**: Partner with leading global companies in AI, cloud, and research for technology development, and with commercial partners for scaled deployment. The company believes the humanoid TAM will reach $38 billion by 2035 and $1 trillion by 2050.

## Why Work Here
- **High-growth environment**: Company grew headcount by 139% in a single year, indicating rapid scaling and opportunity for career advancement. 65+ open roles suggest strong hiring momentum.
- **Talent from top robotics firms**: Team includes alumni from Boston Dynamics, Sanctuary AI, Dyson, Ocado Technology, Arrival, Wayve, and others — offering a deep learning and collaboration environment.
- **Technical focus**: Engineering and technical roles represent 38% of the workforce, with senior-level hires at 23% of the team. The company emphasizes hardware, AI, machine learning, and control systems.
- **Mission-driven**: Clear purpose to automate undesirable, unsafe, and repetitive work — appealing to candidates who want to make a tangible societal impact.
- **Global presence**: Offices in London (HQ), Cambridge (USA), and Burnaby (Canada), plus operations in 16 countries — offering potential for international mobility and remote collaboration.
- **Innovation culture**: Described as a place where engineers and researchers “move from demo to deployment” and “not just in the lab.” The CTO emphasizes building systems that perform in the real world from day one.
- **Office/Hybrid policy**: Not explicitly stated, but the company has physical offices in three countries and a distributed team across 16 nations — likely supports hybrid/remote with in-office collaboration for engineering roles.

## Sources
1. [thehumanoid.ai](https://thehumanoid.ai/)
2. [thehumanoid.ai/about-us/](https://thehumanoid.ai/about-us/)
3. [thehumanoid.ai/team/](https://thehumanoid.ai/team/)
4. [thehumanoid.ai/careers/](https://thehumanoid.ai/careers/)
5. [LinkedIn Company Page](https://www.linkedin.com/company/humanoidai)
6. [Jobs.ashbyhq.com/humanoid](https://jobs.ashbyhq.com/humanoid)

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