Qureos Mentor

Humanoid

Humanoid is the first AI and robotics company in the UK, focused on creating leading, commercially scalable, and safe humanoid robots. The company envisions a future where humanoid robots perform repetitive and monotonous tasks, allowing humans to engage in more meaningful work. By deploying these robots in various industries, Humanoid aims to address labor shortages and enhance human well-being, paving the way for a new era of abundance and innovation in robotics and artificial intelligence.

<div>Here at Humanoid, we believe in a future where robots amplify human potential. That&rsquo;s why we&rsquo;ve set out on a mission to build the world&rsquo;s most capable, commercially-scalable, and safe humanoid robots. We&rsquo;re bringing that mission to life with HMND‑01 Alpha - our rapidly developed humanoid platform now running in real industrial pilots - and we&rsquo;re growing the team to take it even further.<h1 class="jobSectionHeader">
About the Role</h1>
We are seeking a Principal Product Cybersecurity Assurance Engineer with deep expertise in product security, threat modelling, and risk assurance for highly regulated electromechanical systems. In this role, you will lead the delivery of product cybersecurity across Humanoid's HMND 01 platform family &mdash; the Alpha Wheeled industrial robot and the Alpha Bipedal home robot &mdash; both powered by our KinetIQ VLM/VLA-based AI framework. Working alongside product, firmware, autonomy, and hardware teams as part of the Systems Engineering and Architecture Team, you will define and maintain the cybersecurity assurance strategy for all product security activities from first concept through post-market deployment. Security at Humanoid is an engineering discipline inseparable from functional safety and central to our mission of creating the world's most reliable, commercially scalable, and safe humanoid robots. To excel in this position, you must demonstrate the authority to influence security architecture decisions across complex, cross-functional programmes, the rigour to build defensible security cases for novel cyber-physical systems, and the leadership to grow and guide a cross team of security engineers operating at the frontier of robotics.<h1 class="jobSectionHeader">
What You'll Do</h1><ul><li>
Team Leadership &amp; Product Security Delivery<ul><li>
Lead and develop a cross-functional team of security engineers, maintaining accountability for the delivery of product security services within product teams throughout the HMND 01 development lifecycle.</li><li>
Define product security requirements and advise development teams on suitable implementation standards, techniques, and toolchains for embedded and AI-enabled robotic systems.</li><li>
Partner with cross-functional teams to develop security protocols, tools, and processes that keep HMND 01 technologies ahead of emerging threats &mdash; including attack surfaces specific to the KinetIQ AI inference pipeline and cloud-to-robot communication architecture.</li><li>
Own and maintain key security artefacts for audit-ready cybersecurity documentation including Security Management Plans, Threat Analysis and Risk Assessment (TARA) reports, Risk Assessments, and Remediation Action Plans across both platforms.</li></ul>
Security Assurance &amp; Certification<ul><li>
Drive security assurance through the full product lifecycle, ensuring every HMND 01 design is robust, compliant, and resilient. Contribute to the continual improvement of security engineering capability across the organisation.</li><li>
Ensure compliance with cybersecurity obligations under the EU Machinery Regulation 2023/1230 where cyber controls intersect with safety-critical functions and compliance to IEC 62443 (for industrial/OT product security), and the EU Cyber Resilience Act.</li><li>
Provide independent Information Assurance (IA) reviews and risk assessments on complex, high-impact projects &mdash; with particular focus on cyber-physical systems where a digital compromise could result in physical harm to operators or end users.</li><li>
Review and provide guidance on security risk assessments, risk mitigation plans, mitigation gap analysis, and security management documentation in support of system cybersecurity certification.</li></ul>
Incident Response &amp; Lifecycle Security<ul><li>
Establish and maintain a Product Security Incident Response (PSIR) process, encompassing coordinated vulnerability disclosure, patch deployment pipelines, and post-field incident analysis.</li><li>
Define and oversee security monitoring requirements for deployed fleets, ensuring field data feeds back into risk files and security artefacts in line with post-market surveillance obligations.</li></ul>
Commercial &amp; Bid Support<ul><li>
Support the production of work package descriptions and cost estimates for product bids, services, and proposals that include product security scope.</li><li>
Represent Humanoid's security posture in customer and partner engagements, including regulatory consultations and certification body interactions.</li></ul></li></ul><h1 class="jobSectionHeader">
What We're Looking For</h1><ul><li>
Proven, hands-on experience with ISO 27001/27004/27005 and the NIST Risk Management Framework (RMF), applied to regulated hardware or embedded product programmes.</li><li>
Experience owning a security risk management system for highly regulated, safety-critical products &mdash; with background drawn from automotive, commercial vehicle, or industrial automation environments.</li><li>
Working knowledge of IEC 62443, with the ability to adapt ISO/SAE 21434 lifecycle methodologies to robotic or electromechanical product context.</li><li>
Solid understanding of engineering development lifecycles and how the product cybersecurity specialism aligns with systems engineering, functional safety, and hardware/software co-development.</li><li>
Ability to interpret Penetration Test reports and author Remediation Action Plans that address identified vulnerabilities in a structured, risk-prioritised manner.</li><li>
Clear, structured communication skills &mdash; able to articulate complex security risk arguments to both technical engineers and executive stakeholders with equal confidence.</li></ul>
Preferred:<ul><li>
Familiarity with Threat Analysis and Risk Assessment (TARA) or equivalent threat modelling methodologies (STRIDE, PASTA) applied to embedded or OT/IT convergent systems.</li><li>
Understanding of secure-by-design principles for AI/ML-enabled systems, including securing inference pipelines, model integrity, and cloud-to-edge communication paths.</li><li>
Exposure to CAN bus, Ethernet backbone, or wireless interface security in mobile, vehicular, or robotic systems.</li><li>
Experience contributing to or establishing a Product Security Incident Response (PSIRT) process or coordinated vulnerability disclosure programme.</li><li>
Knowledge of UL 4600, UL 3300, or ISO 13482 and an appreciation of how cybersecurity evidence integrates into safety case arguments.</li><li>
Prior engagement with certification bodies (TUV, UL, BSI) or standards development organisations (ISO TC 184, IEC TC 65, SAE, IEEE RAS).</li></ul><h1 class="jobSectionHeader">
What We Offer</h1><ul><li>
Competitive equity: stock options with meaningful upside as we scale.</li><li>
30+ days off, including 23 days annual leave, all UK bank holidays, and additional company closure days (including Christmas&ndash;New Year shutdown).</li><li>
Private healthcare, including virtual and in-person care.</li><li>
Pension scheme with 8% total contribution (5% employee, 3% employer) on full earnings.</li><li>
Free daily breakfast, catered lunch, and snacks in-office.</li><li>
Work at the frontier - collaborate daily with world-class engineers, researchers, and product experts building the next generation of AI and humanoid robotics.</li><li>
Real ownership - direct access to founding leadership, meaningful input on product direction, and the ability to drive key initiatives from day one.</li></ul></div>

Principal Product Cybersecurity Assurance

<div>
 
 Here at Humanoid, we believe in a future where robots amplify human potential. That&rsquo;s why we&rsquo;ve set out on a mission to build the world&rsquo;s most capable, commercially-scalable, and safe humanoid robots. We&rsquo;re bringing that mission to life with HMND‑01 Alpha - our rapidly developed humanoid platform now running in real industrial pilots - and we&rsquo;re growing the team to take it even further.
 
 
 
 
 
 
 About The Role
 
 
 
 We're hiring a
 
 VLA Pre-training Engineer (Deep Learning)
 
 to join our Autonomy team based in London.
 
 
 In this role you will you will work on all aspects of training capable policies, be it pre-training of a base model on a diverse multi-embodiment corpus of trajectories, fine-tuning a policy to perform a specific task well, curating data collection processes or exploring productive ways to generate and use synthetic data. This is primarily a deep learning-focused role, so we are looking for experience solving real problems using modern neural networks, while experience in robotics isn&rsquo;t strictly required. However if you don&rsquo;t have such experience, be prepared that you&rsquo;d need to familiarize yourself with a new domain quickly.
 
 
 
 
 
 
 What You'll Do
 
 
 <ul>
 <li>
 Post-train policies via behaviour cloning and RL; own the full loop from data to deployment.
 </li>
 <li>
 Partner with the Data Collection team to drive collecting new data: specify what good data looks like, identify failure modes, ensure diversity and coverage.
 </li>
 <li>
 Work closely with external partners to ensure steady supply of high-quality pretraining-scale data.
 </li>
 <li>
 Run pre-/mid-/post-training on VLA stack; explore new modalities and architecture changes.
 </li>
 <li>
 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.
 </li>
 <li>
 Work with MLOps &amp; Data Platform teams to scale distributed training and optimize models for real‑time edge inference.
 </li>
 </ul>
 
 
 
 
 
 What We're Looking For
 
 
 <ul>
 <li>
 3+ years building deep‑learning systems (industry or research) with shipped models or published artifacts to show for it.
 </li>
 <li>
 Deep hands‑on experience with at least one of: LLMs, VLMs, or image/video generative models &mdash; architecture, training, and inference.
 </li>
 <li>
 Experience with deep learning infrastructure: streaming datasets, checkpointing &amp; state management, distributed training strategies.
 </li>
 <li>
 Strong Python + PyTorch/JAX; you can profile, debug numerics, and write maintainable research code.
 </li>
 <li>
 Familiarity with modern software engineering practices.
 </li>
 <li>
 You document experiments clearly and communicate trade‑offs crisply.
 </li>
 </ul>
 
 
 Nice to have
 
 
 <ul>
 <li>
 Robotics or autonomous driving experience.
 </li>
 <li>
 Experience applying RL to LLMs or robotics.
 </li>
 <li>
 Experience with VLA (vision-language-action) models.
 </li>
 <li>
 Proven productization of deep nets (latency/throughput constraints, telemetry, on‑device optimization).
 </li>
 <li>
 Publications at top-tier deep learning conferences or equivalent open‑source contributions.
 </li>
 <li>
 Familiarity with OpenVLA, Physical Intelligence (&pi;) models, or similar open source VLA frameworks.
 </li>
 </ul>
 
 
 
 
 
 What We Offer
 
 
 <ul>
 <li>
 ompetitive equity: stock options with meaningful upside as we scale.
 </li>
 <li>
 30+ days time off, including 23 days annual leave, all UK bank holidays, and additional company closure days (including Christmas&ndash;New Year shutdown).
 </li>
 <li>
 Private healthcare, including virtual and in-person care.
 </li>
 <li>
 Pension scheme with 8% total contribution (5% employee, 3% employer) on full earnings.
 </li>
 <li>
 Free daily breakfast, catered lunch, and snacks in-office.
 </li>
 <li>
 Work at the frontier - collaborate daily with world-class engineers, researchers, and product experts building the next generation of AI and humanoid robotics.
 </li>
 <li>
 Real ownership - direct access to founding leadership, meaningful input on product direction, and the ability to drive key initiatives from day one.
 </li>
 </ul>
</div>

VLA Pre-training Engineer (Deep Learning)

<div>Here at Humanoid, we believe in a future where robots amplify human potential. That&rsquo;s why we&rsquo;ve set out on a mission to build the world&rsquo;s most capable, commercially-scalable, and safe humanoid robots. We&rsquo;re bringing that mission to life with HMND‑01 Alpha - our rapidly developed humanoid platform now running in real industrial pilots - and we&rsquo;re growing the team to take it even further.<h2 class="jobSectionHeader">
About the role:
</h2>We are looking for a Software Engineer to work on the systems that let operators author, deploy, and manage robot workflows at scale. This sits at the intersection of backend infrastructure and product - you'll build the services that coordinate fleets of robots, the tooling that lets operators express what they want robots to do, and the interfaces that give visibility into what's actually happening on the floor.
This is a full-stack role with a strong backend lean. You'll work closely with the robotics, AI, and product teams to build systems that are real-time, multi-tenant, and mission-critical.<h2 class="jobSectionHeader">
What You&rsquo;ll Do</h2><ul><li>
Build and maintain backend services that coordinate robot fleets at runtime: workflow state management, event logging, and the APIs that robots, operators, and third-party systems use to interact with the platform</li><li>
Develop and evolve the workflow authoring experience - tooling that lets operators define, deploy, and incrementally refine robot workflows in natural language, without needing to understand the underlying representation</li><li>
Build on-robot services that enable remote control, workflow execution, state reporting, and diagnostics</li><li>
Own the data infrastructure that tracks workflow execution: event logs, conformance metrics, and the audit trails that let operators understand what robots are doing and why</li><li>
Build and maintain reliable, secure cloud infrastructure for running these services, including deployment pipelines, observability, and alerting</li><li>
Implement testing and validation pipelines to catch regressions across the UI, backend, and on-robot services - including simulation-based workflow validation before changes hit production</li></ul><h2 class="jobSectionHeader">
What We&rsquo;re Looking For</h2><ul><li>
Strong backend engineering skills in Python, Go, or similar</li><li>
Solid understanding of API design, data modelling, and the tradeoffs in distributed systems (consistency, concurrency, fault tolerance)</li><li>
Experience with cloud infrastructure and deployment: containerisation, CI/CD, infrastructure-as-code</li><li>
Comfort working across the stack from frontend to backend</li><li>
Experience with observability and alerting in systems where failures have real operational consequences</li><li>
Good instincts for where complexity should live and how to keep systems debuggable and understandable as they grow</li></ul><h2 class="jobSectionHeader">
Nice To Have</h2><ul><li>
Familiarity with workflow engines, state machines, or coordination systems &mdash; ideally in a multi-agent or fleet context</li><li>
Experience building operator-facing tooling: dashboards, authoring UIs, or systems that translate human intent into structured actions</li><li>
Exposure to LLM-based agentic systems, particularly using AI to generate or modify structured representations from natural language</li><li>
Experience integrating with third-party enterprise systems (WMS, ERP, or similar)</li><li>
Background in robotics or real-time systems where execution state and side-effects need to be managed carefully</li></ul><h1 class="jobSectionHeader">
What We Offer</h1><ul><li>
Competitive equity: stock options with meaningful upside as we scale.</li><li>
30+ days off, including 23 days annual leave, all UK bank holidays, and additional company closure days (including Christmas&ndash;New Year shutdown).</li><li>
Private healthcare, including virtual and in-person care.</li><li>
Pension scheme with 8% total contribution (5% employee, 3% employer) on full earnings.</li><li>
Free daily breakfast, catered lunch, and snacks in-office.</li><li>
Work at the frontier - collaborate daily with world-class engineers, researchers, and product experts building the next generation of AI and humanoid robotics.</li><li>
Real ownership - direct access to founding leadership, meaningful input on product direction, and the ability to drive key initiatives from day one.</li></ul></div>

Software Engineer - Workflow Authoring & Deployment

<div>Here at Humanoid, we believe in a future where robots amplify human potential. That&rsquo;s why we&rsquo;ve set out on a mission to build the world&rsquo;s most capable, commercially-scalable, and safe humanoid robots. We&rsquo;re bringing that mission to life with HMND‑01 Alpha - our rapidly developed humanoid platform now running in real industrial pilots - and we&rsquo;re growing the team to take it even further.<h1 class="jobSectionHeader">
About the Role:</h1>
We are looking for a Software Engineer to own the device software and data pipeline for our UMI data collection devices - handheld gripper systems used by human operators to demonstrate manipulation tasks. The data they produce is used to train our robots, so the quality of what you ship determines the quality of robots we deploy.
This is a deeply technical, hands-on role. You will write production-grade device software, build reliable sensor fusion and recording pipelines, and own the validation tooling that keeps our training datasets clean. You will work closely with hardware, AI, and data collection teams.
<h2 class="jobSectionHeader">What You&rsquo;ll Do:</h2><ul><li>
Develop and maintain device software across the full episode lifecycle: session initialisation, per-sensor stream management, episode recording, and graceful shutdown</li><li>
Integrate and synchronise sensor streams - wrist and head cameras, 6-DOF pose trackers, gripper aperture encoders, and optionally force/torque sensors - into temporally-aligned, policy-consumable trajectories</li><li>
Define and maintain the data contract between UMI devices and the AI team: stream formats, episode packaging, metadata schemas, and the interface between raw recordings and training pipelines</li><li>
Build and maintain data validation tooling that detects dropped frames, timing jitter, pose tracking loss, image quality degradation, and sensor faults before corrupt episodes enter the training dataset</li><li>
Own operator-facing device software: status indication, start/stop/cancel episode controls, and clear feedback when a session needs to be retried</li><li>
Support field data collection sessions - deploying devices to operators, validating data quality in situ, and iterating quickly when issues surface during collection</li><li>
Debug integration failures on device hardware: camera driver issues, bus bandwidth saturation, tracker calibration drift, compute thermal throttling, and storage write failures mid-episode</li></ul><h2 class="jobSectionHeader">
We&rsquo;re Looking For:</h2><ul><li>
Experience in embedded or device-level software in a robotics or sensing context - writing code that runs on the device, not just talking to it</li><li>
Proficiency in C++ and/or Python for real-time sensor drivers, inter-process communication, and data recording pipelines</li><li>
Solid understanding of multi-modal sensor synchronisation - timestamps, hardware triggers, clock drift - and the practical consequences of getting it wrong for downstream ML</li><li>
Familiarity with camera pipelines and the difference between what a sensor reports and what actually lands on disk with correct timing</li><li>
Strong instincts around data quality and dataset hygiene - you are uncomfortable shipping episodes with frame drops, tracking loss, or misaligned streams</li><li>
Proven ability to debug on real hardware: you read logs, attach profilers, and can diagnose whether a problem is a driver, a bus, or a timing issue</li></ul><h2 class="jobSectionHeader">
Nice to have:</h2><ul><li>
Experience with 6-DOF pose tracking systems (VIO, optical trackers, or similar) and their common failure modes</li><li>
Familiarity with ML training data formats and what an AI team actually needs from a recorded episode - understanding the consumer of the data you produce</li><li>
Exposure to operator-facing tooling for data collection: session management, per-episode quality summaries, rejection and retry workflows</li><li>
Experience scaling device software from a small number of prototype units to many devices operated by non-engineers in the field</li></ul><h1 class="jobSectionHeader">
What We Offer</h1><ul><li>
Competitive equity: stock options with meaningful upside as we scale.</li><li>
30+ days off, including 23 days annual leave, all UK bank holidays, and additional company closure days (including Christmas&ndash;New Year shutdown).</li><li>
Private healthcare, including virtual and in-person care.</li><li>
Pension scheme with 8% total contribution (5% employee, 3% employer) on full earnings.</li><li>
Free daily breakfast, catered lunch, and snacks in-office.</li><li>
Work at the frontier - collaborate daily with world-class engineers, researchers, and product experts building the next generation of AI and humanoid robotics.</li><li>
Real ownership - direct access to founding leadership, meaningful input on product direction, and the ability to drive key initiatives from day one.</li></ul></div>

Software Engineer - Data & Sensors

<div>Here at Humanoid, we believe in a future where robots amplify human potential. That&rsquo;s why we&rsquo;ve set out on a mission to build the world&rsquo;s most capable, commercially-scalable, and safe humanoid robots. We&rsquo;re bringing that mission to life with HMND‑01 Alpha - our rapidly developed humanoid platform now running in real industrial pilots - and we&rsquo;re growing the team to take it even further.<h1 class="jobSectionHeader">
About the Role</h1>
We are looking for a Software Engineer to own the build system and CI infrastructure that every engineer at Humanoid depends on every day. This is foundational work: a slow, unreliable, or opaque build pipeline is a tax on the entire engineering organisation, and getting it right directly determines how fast we can ship robots.
We are investing heavily in build infrastructure - hermetic, incremental, fully cached builds across a complex multi-target monorepo spanning firmware, robot software, simulation, and cloud - and we need someone to drive that work and own the system it produces.
This is a deeply technical infrastructure role. You will work closely with every engineering team in the organisation, and the quality of your work will be felt by every person who opens a PR.<h2 class="jobSectionHeader">
What You&rsquo;ll Do</h2><ul><li>
Build and maintain CI pipelines in GitHub Actions: incremental test selection based on affected targets, nightly full builds, and clear triage tooling when main goes red</li><li>
Instrument the build: CI telemetry, dashboards showing build and test times broken down by job type, branch, and author &mdash; so we stop flying blind on build health</li><li>
Define and enforce the policies that keep main green: merge queue configuration, PR gating, and the on-call process when broken builds block other engineers</li><li>
Own and maintain the remote build cache infrastructure, ensuring cache correctness, invalidation on environment changes, and read-only promotion from main only</li><li>
Own the developer environment story &mdash; local builds, dependency management, and the tooling that lets engineers iterate quickly without fighting their environment</li><li>
Maintain and evolve the dependency mirroring infrastructure (apt, PyPI, and other upstream registries) so that external package availability never blocks a build</li></ul><h2 class="jobSectionHeader"> 
What We&rsquo;re Looking For</h2><ul><li>
Solid experience with build systems - ideally Bazel, but deep knowledge of CMake or similar is fine; the instincts matter more than the specific tool</li><li>
Experience designing and operating CI pipelines at scale: incremental testing, artifact caching, runner management, and keeping feedback loops short</li><li>
Strong understanding of hermetic build environments</li><li>
Comfort debugging complex build failures across multiple languages and toolchains</li><li>
Experience with dependency management and the tradeoffs between reproducibility, speed, and upstream risk</li><li>
Good instincts for developer experience</li></ul><h2 class="jobSectionHeader">
Nice To Have</h2><ul><li>
Familiarity with ROS/ROS2 build tooling (colcon, ament, CMake)</li><li>
Familiarity with Kubernetes: self-hosted runners, ARC</li><li>
Experience with GitHub Actions at scale</li><li>
Background in robotics or embedded systems where build artifacts span multiple target architectures and deployment environments</li></ul><h1 class="jobSectionHeader">
What We Offer</h1><ul><li>
Competitive equity: stock options with meaningful upside as we scale.</li><li>
30+ days time off, including 23 days annual leave, all UK bank holidays, and additional company closure days (including Christmas&ndash;New Year shutdown).</li><li>
Private healthcare, including virtual and in-person care.</li><li>
Pension scheme with 8% total contribution (5% employee, 3% employer) on full earnings.</li><li>
Free daily breakfast, catered lunch, and snacks in-office.</li><li>
Work at the frontier - collaborate daily with world-class engineers, researchers, and product experts building the next generation of AI and humanoid robotics.</li><li>
Real ownership - direct access to founding leadership, meaningful input on product direction, and the ability to drive key initiatives from day one.</li></ul></div>

Platform Engineer - Build and CI