---
title: 'Director of Autonomy - Biped at Humanoid'
canonical: 'https://feeny.ai/job/director-of-autonomy-biped-humanoid-us-san-diego-sjgj2p9e580z'
type: 'job'
last_seen: '2026-11-05'
---

# Director of Autonomy - Biped at Humanoid

- **Company:** [Humanoid](https://feeny.ai/companies/humanoid)
- **Location:** US San Diego, CA
- **Employment:** full-time
- **Work type:** onsite
- **Posted:** 2026-10-09
- **Last confirmed live:** 2026-11-05
- **Apply:** https://jobs.ashbyhq.com/humanoid/40787896-1d68-4a6b-ba02-a4186c9325d8

## 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 - our rapidly developed humanoid platform being deployed in real industrial environments - and we’re growing the team to take it even further.

## About The Role

As Director of Autonomy at Humanoid, you will lead the team that teaches our bipedal platform to perform locomanipulation tasks in homes and service environments: tidying a room, loading and unloading a dishwasher, putting groceries away, folding laundry, and similar tasks. The output of your team is capabilities that run reliably on real robots and pass our evals, not papers or one-off demos. This is a player-coach role: you own the roadmap, hiring, and delivery, while also training policies, curating data, and debugging failures on the robot yourself. That hands-on work is how you lead: it's how you find what slows the team down and fix it for everyone.

This role sits at the intersection of applied deep learning, robotics, and people leadership, working closely with the Controls team on whole-body teleoperation and combining RL controllers with learned policies, and with the Core Technology team on foundation model pre-training for five-finger dexterity and RL methods. If you have hands-on experience with real robot hardware, a track record in applied deep learning, and have led engineers doing this kind of work, we want to hear from you.

## What You'll Do

- Own The Capability Roadmap: Work with product to identify use-case priority, choose the execution strategy, define the evals, and deliver on the agreed timeline.
- Lead The Team: Hire, develop, and manage a team of robot learning engineers; set engineering and experimental standards; run day-to-day prioritization.
- Co-Own The System 0/1 Interface: Agree with the Controls team on what the policy commands (end-effector targets, root velocity, pelvis height, foot targets, hand joint targets), debug failures across that boundary, and push requirements into the whole-body control roadmap.
- Partner On Data Strategy: Specify what good data looks like for bipedal locomanipulation with data collection and external acquisition organizations, ensure diversity and coverage, iterate on operator instructions, and supervise collection on the biped.
- Drive Sim-To-Real Transfer: Work with the Simulation team to set up RL training on the digital twin for bipedal tasks, then iterate on reward and simulation quality to ensure transfer to the real world.
- Shape Base Model Development: Feed bipedal requirements — embodiment coverage in the pretraining mixture, action representations, latency budgets — into the VLA Core Technology team's base model development, and adopt new base models as they land.
- Inform Hardware Design: Interface with the Hardware Design team so findings about hands, arms, and legs on the current generation are reflected in future designs.
- Report On Progress: Communicate progress to leadership in terms of capabilities working on the robot, eval results, and failure analysis.

## What We're Looking For

- 5+ years working on robots (industry or research) with shipped artifacts to show for it, including learned manipulation or locomanipulation policies deployed on real hardware.
- Experience leading a team of 5+ engineers doing applied robot learning, including hiring and people management, with capabilities delivered to a deadline.
- Hands-on today: you've trained and debugged policies within the last year and intend to keep doing so, and can curate data, post-train a policy, and diagnose failures without delegating that work.
- Experience post-training VLA-class policies (autoregressive, diffusion, or flow-matching based) via behavior cloning and/or RL.
- Solid understanding of the modern teleoperation and low-level control stack — whole-body control, inverse kinematics, RL locomotion controllers — and the ability to tell whether a failure lives in the policy, the controller, or the data.
- Familiarity with deep learning infrastructure: streaming datasets, checkpointing and state management, distributed training, PyTorch or JAX.
- Strong grounding in modern software engineering practices, with the ability to document experiments clearly and communicate trade-offs crisply to engineers and leadership.

## Nice To Have

- Experience with multi-fingered dexterous hands: teleoperation and retargeting, tactile sensing, in-hand manipulation.
- Experience with legged platforms: bipedal locomotion, whole-body control, humanoid teleoperation.
- Experience applying RL to robotics problems in simulation or on real robots.
- Familiarity with Physical Intelligence (π) models, NVIDIA GR00T, or similar open VLA frameworks.
- Publications at top-tier robotics or deep learning conferences (CoRL, RSS, ICRA, NeurIPS) or equivalent open-source contributions.

## What We Offer

- Comprehensive health coverage for US‑based employees, including fully paid medical, dental, and vision insurance, with virtual care and employee assistance resources.
- Meaningful time off to rest and recharge: 23 days of PTO (accrued), separate sick leave, and paid company holidays.
- 401(k) retirement plan with 4% employer match.
- Competitive equity: stock options with meaningful upside as we scale.
- Free daily catered lunch, snacks, and drinks in‑office.
- Collaboration with top‑tier engineers, researchers, and product experts in AI and robotics.
- Freedom to influence the product and own key initiatives.

For this role in California, the expected base salary range is $300,000-$450,000 USD per year; your placement in that range depends on how experience maps to our internal leveling.

## 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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- [Test and Validation Engineer - Contract](https://feeny.ai/job/test-and-validation-engineer-contract-humanoid-canada-vancouver-r5kewqy9gbdd) — Canada Vancouver, Canada
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