Develops commercially scalable humanoid robots combining advanced AI and modular hardware to automate real‑world tasks.
Lead strategy & development of multi-modal VLA systems for humanoid robots
3 days ago ago
Expert & Leadership (13+ years)
Full Time
London Area, United Kingdom
Hybrid
Company Size
130 Employees
Service Specialisms
Design
Engineering
AI
Hardware
Software
Supply Chain & Logistics
Cost Engineering
Manufacturing
Sector Specialisms
Healthcare
Elder Care
Manufacturing
Supply Chain
Retail
Logistics
Industrial
Personal Assistance
Role
Description
multi-modal training
sensor integration
distributed training
edge deployment
representation learning
reinforcement learning
Lead large-scale post-training of multi-modal LLM / VLM / VLA systems; continuously integrate new sensor modalities (vision, audio, proprioception, LiDAR, point cloud, …).
Collaboration with top‑tier engineers, researchers, and product experts in AI and robotics
Partner with MLOps and Data Platform teams to scale distributed training and optimise models for real-time edge deployment.
Set and drive the strategy for representation learning, behaviour cloning and reinforcement learning (RL).
Build always-on pipelines that collect sim + tele-op logs, store them in a versioned lake, transform / label streams with weak supervision, curate balanced datasets and run an evaluation loop that feeds fresh failure cases back into training.
Hire, mentor and unblock a small, elite team of research scientists and engineers.
Requirements
llm
vlm
openvla
deep learning
team leadership
autonomous driving
Demonstrated record of shipping to real robots or vehicles and iterating via data-flywheel loops.
Experience in autonomous vehicle control and planning.
Hands-on experience with LLM / VLM architecture design, billion-parameter training and fine-tuning.
Research or open-source work in multi-modal transformers, diffusion control, world models.
Proven robotics, autonomous driving or LLMs expertise (behaviour cloning, actor–critic, offline RL) applied to robotics or autonomous driving.
Freedom to influence the product and own key initiatives
Deployment on humanoid or legged robots.
6+ years building deep-learning systems, 2+ years technical team leadership.
Familiarity with OpenVLA, Physical Intelligence (π) models or other open-source VLA frameworks.
Benefits
Competitive salary plus participation in our Stock Option Plan
Travel opportunities to our Vancouver and Boston offices
Office perks: free breakfasts, lunches, snacks, and regular team events
Paid vacation with adjustments based on your location to comply with local labor laws
The company was established by Artem Sokolov to address real-world automation challenges with next-gen robots.
130+ Engineers
Experienced Team
The company has assembled a team of world-class engineers and researchers across multiple locations.
2025 Launch
Prototype Release
Planned to release the HMND 01 prototype for market testing and deployment.
15 kg Capacity
Load-bearing Ability
The robot can carry up to 15 kg, walk at 1.5 m/s, and operate for 4 hours on a single charge. It stands at 175 cm tall with both wheeled and bipedal configurations.
Blends advanced AI, multimodal vision reasoning, and modular hardware into a robust platform targeting logistics, manufacturing, and retail.
The company pivots on commercial impact—solving repetitive physical tasks in real settings, not just lab experiments.
A cinematic teaser video set the tone for its vision: human-robot coexistence in everyday environments.
A standout is its modular design allowing interchangeable platforms—wheeled or legged—aimed at rapid and affordable deployment.
Culture + Values
We foster a collaborative environment where we build, learn, and grow together.
We believe in developing technology that benefits humanity.
Our team is empowered to innovate, create, and execute with a shared passion for progress.
We encourage open communication and transparency in all our efforts.
We are driven by curiosity and a desire to solve the world's toughest problems.
Environment + Sustainability
2030
Net Zero Target
Aiming to reach net zero carbon emissions by the year 2030.
Strive to minimize our carbon footprint through energy-efficient technology and sustainable practices.
Prioritize eco-friendly materials and processes in our product development.
Support renewable energy initiatives and actively reducing waste in our operations.
Goal is to be a leader in sustainability within the tech industry by fostering innovation with minimal environmental impact.
Inclusion & Diversity
Promotes a diverse and inclusive workplace where everyone feels valued and respected.
Committed to equal opportunity and creating a space where all employees can thrive.
Strives to reflect diversity in hiring practices and encourage diverse perspectives in teams.