---
title: 'Autonomy Engineer - VLA Pre-training at Humanoid'
canonical: 'https://feeny.ai/job/autonomy-engineer-vla-pre-training-humanoid-us-san-diego-axm9pwqdfhbv'
type: 'job'
last_seen: '2026-10-15'
---

# Autonomy Engineer - VLA Pre-training at Humanoid

- **Company:** [Humanoid](https://feeny.ai/companies/humanoid)
- **Location:** US San Diego, CA
- **Employment:** full-time
- **Work type:** onsite
- **Posted:** 2026-10-14
- **Last confirmed live:** 2026-10-15
- **Apply:** https://jobs.ashbyhq.com/humanoid/42ece2fe-54fa-4786-8ecb-95e066be7c32

## 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 an Autonomy Engineer focused in VLA Pre-training, you will work on all aspects of training capable policies. You'll pre-train base models on a diverse, multi-embodiment corpus of trajectories, fine-tune policies to excel at specific tasks, shape data collection processes, and explore effective ways to generate and use synthetic data. This is primarily a deep learning role, so we're looking for experience solving real-world problems with modern neural networks. Robotics experience isn't strictly required, but if you're coming from outside the field, be prepared to get up to speed on a new domain quickly.

## What You'll Do

- Post-train policies via behavior cloning and RL; own the full loop from data to deployment.
- Partner with the Data Collection team to drive collecting new data: specify what good data looks like, identify failure modes, ensure diversity and coverage.
- Work closely with external partners to ensure steady supply of high-quality pretraining-scale data.
- Run pre-/mid-/post-training on VLA stack; explore new modalities and architecture changes.
- Build and maintain continuous pipelines: ingest synthetic data and teleop logs, version them, apply weak‑supervision labelling, curate balanced datasets, and auto‑surface fresh failure cases into retraining.
- Work with MLOps & Data Platform teams to scale distributed training and optimize models for real‑time edge inference.

## What We're Looking For

- 3+ years building deep‑learning systems (industry or research) with shipped models or published artifacts to show for it.
- Deep hands‑on experience with at least one of: LLMs, VLMs, or image/video generative models — architecture, training, and inference.
- Experience with deep learning infrastructure: streaming datasets, checkpointing & state management, distributed training strategies.
- Strong Python + PyTorch/JAX; you can profile, debug numerics, and write maintainable research code.
- Familiarity with modern software engineering practices.
- You document experiments clearly and communicate trade‑offs crisply.

## Nice to have

- Robotics or autonomous driving experience.
- Experience applying RL to LLMs or robotics.
- Experience with VLA (vision-language-action) models.
- Proven productization of deep nets (latency/throughput constraints, telemetry, on‑device optimization).
- Publications at top-tier deep learning conferences or equivalent open‑source contributions.
- Familiarity with OpenVLA, Physical Intelligence (π) models, or similar open source VLA frameworks.

## 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 employer match.
- Equity included–we believe builders should share in what they build.
- 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 $180,000–$300,000 USD per year; your placement in that range depends on how your 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)

## Other roles at Humanoid

- [Senior Machine Learning Research Engineer](https://feeny.ai/job/senior-machine-learning-research-engineer-humanoid-london-hxe7d1dzwkq2) — London, United Kingdom
- [Senior Electrical Design Engineer](https://feeny.ai/job/senior-electrical-design-engineer-humanoid-us-boston-xsws5bc26e70) — US Boston, MA
- [Prototype Engineer](https://feeny.ai/job/prototype-engineer-humanoid-canada-vancouver-8q47n6t9cttp) — Canada Vancouver, Canada
- [Senior Test  and Validation Engineer](https://feeny.ai/job/senior-test-and-validation-engineer-humanoid-canada-vancouver-z93vt2r30q49) — Canada Vancouver, Canada
- [Warehouse Operative Specialist](https://feeny.ai/job/warehouse-operative-specialist-humanoid-canada-vancouver-q6hg0sxc5x2k) — Canada Vancouver, Canada
- [Senior General Mechanical Design Engineer](https://feeny.ai/job/senior-general-mechanical-design-engineer-humanoid-canada-vancouver-egfdqs5n1nek) — Canada Vancouver, Canada
- [Senior Actuator Mechanical Design Engineer](https://feeny.ai/job/senior-actuator-mechanical-design-engineer-humanoid-canada-vancouver-2wybjffgzk3c) — Canada Vancouver, Canada
- [Senior Firmware and Embedded Software Engineer](https://feeny.ai/job/senior-firmware-and-embedded-software-engineer-humanoid-canada-vancouver-k66gncrpem53) — Canada Vancouver, Canada
- [Mechanical Design Engineer - Robotic Hand](https://feeny.ai/job/mechanical-design-engineer-robotic-hand-humanoid-canada-vancouver-gh8tcpr351rr) — Canada Vancouver, Canada
- [Treasury Manager](https://feeny.ai/job/treasury-manager-humanoid-london-5szpvajax22s) — London, United Kingdom