Jobs at Humanoid

Own planning and execution of complex humanoid robotics programs from concept through deployment. Coordinate globally distributed hardware and software teams, manage scope, schedule, cost, risks, dependencies, suppliers, and cross-functional workstreams. Drive alignment, remove blockers, communicate with stakeholders, and apply technical judgment across systems, safety, mechanical, electrical, firmware, software, AI/ML, integration, testing, production, and supply chain.

Leads global government relations, public affairs, and policy strategy for humanoid robotics across the UK, EU, US, and Canada. Develops regulatory pathways, policy positions, public funding opportunities, and the public-interest case for robotics. Builds relationships with governments, regulators, standards bodies, and industry associations; advises leadership on political developments; represents the company publicly; and establishes and leads the government relations function.

Lead development of spatial intelligence for humanoid robots, including state estimation, mapping, localization, 3D scene understanding, spatial memory, and semantic navigation. Train and deploy large multimodal models and integrate them into low-latency robot systems running on edge hardware. Drive perception research from model evaluation and dataset benchmarking through reliable production implementation, collaborating across engineering and research teams.

Build and lead a global Supplier Quality Assurance function for high-reliability humanoid robotics. Define SQA strategy, governance, KPIs, audits, incoming inspection, supplier development, SCAR/MRB/NCR processes, FAI and process capability approval, and cross-functional quality leadership across multi-site operations.

Supports the CFO by preparing meeting materials, capturing decisions, tracking action items, coordinating finance stakeholders, reviewing financial documents, and producing clear follow-up communications. Maintains a master tracker, anticipates meeting needs, escalates blockers, and handles confidential information with discretion. The role requires finance literacy, excellent organisation and writing skills, strong follow-through, and proficiency with Microsoft Office or Google Workspace.

Own business development and sales for robotics solutions across warehouse, logistics, automotive, and manufacturing markets. Lead the full sales cycle, secure pre-sales, partnerships, commercial agreements, and pre-orders, and build relationships with industry decision-makers. Develop ROI analyses and business cases, exceed sales targets, collaborate with product and engineering teams, monitor market trends, and manage P&L and financial modeling in a fast-paced environment.

Own investor relations, communications, cap-table management, board reporting, governance records, fundraising support, diligence, and investor-relations infrastructure. The role partners with the CFO, founders, Legal, Finance, and People teams to build scalable reporting processes, maintain investor relationships, prepare financial narratives and board materials, and ensure compliant disclosures as the company grows toward IPO readiness.

Own global treasury, liquidity, cash forecasting, FX and financial risk management across multiple entities and currencies. Source and structure debt financing, manage lender relationships, support equity fundraising, lead investor relations, maintain the cap table, and manage diligence data rooms. Establish treasury policies, controls, governance, and scalable processes while ensuring regulatory and reporting compliance. The role operates autonomously in a fast-growing, venture-backed robotics company and reports to the CFO.

Own monthly and statutory reporting, group consolidation, close processes, technical accounting, inventory and manufacturing cost accounting, cash flow reporting, audits, and UK statutory accounts. Build scalable controls, accounting policies, reporting processes, and finance systems integrations across global entities. The role requires managing multi-currency consolidation, intercompany eliminations, IFRS and FRS 102 reporting, and supporting ERP and automation improvements in a high-growth robotics company.

Manage finance operations across global entities, with primary responsibility for accounts payable, supplier onboarding, invoice processing, payment runs, expenses, reconciliations, and month-end close support. Produce AP ageing, supplier spend, and working capital analysis while improving purchasing controls, payment terms, and process efficiency. Support automation, ERP and spend-platform integrations, PO-based purchasing, three-way matching, and documentation as the company scales manufacturing operations.

Lead end-to-end supply chain operations for the London site, including procurement, logistics, warehouse, inventory, material flow, and procure-to-pay execution. Manage supplier performance, negotiations, compliance, expediting, SAP data accuracy, inbound logistics, and continuous improvement. Lead a multidisciplinary team, establish operational KPIs, ensure material availability for engineering and production, and serve as the site’s primary supply chain escalation point.

Own end-to-end HR operations, including onboarding, offboarding, employee data, contracts, HRIS administration, payroll inputs, benefits, compliance, audits, and vendor relationships. Improve and automate HR workflows, maintain accurate records, ensure UK employment-law compliance, and serve as an escalation point for employee queries. Partner with HR, Talent Acquisition, Payroll, Finance, and Legal to build scalable employee lifecycle processes in a fast-growing organization.

Own software serviceability for humanoid robots: design and validate diagnostics, firmware/bootloader recovery, remote-diagnostics content, tooling for fast fault localization, and act as Services interface to R&D. Validate OTA, calibration, and repair procedures and support new service introductions.

Optimize and deploy neural-network control policies for humanoid robots: profile and remove inference bottlenecks, port models to new hardware, implement custom kernels, quantize models with minimal quality loss, and propose architecture changes to improve latency and memory usage.

Lead employer branding to attract technical talent by building community relationships, running events (hackathons, meetups, university partnerships), creating content with PR & Marketing, improving careers site and employee advocacy, and measuring impact to continuously optimize talent attraction.

Develop and deploy robot manipulation capabilities by training and fine-tuning policies (behavior cloning and RL), curating and preprocessing datasets, iterating simulation/digital twin training, expanding observation/action spaces, partnering with teleoperation, controls and hardware teams to ensure smooth transfer and improve real-world performance.

Lead ownership of ML models and infrastructure lifecycle: develop, deploy, monitor, and improve ML systems. Build CI/CD for software and ML workflows, automate orchestration and environment management, ensure scalability, reliability, observability, and security, troubleshoot production issues, and document operational procedures while collaborating with engineers, data scientists, and product teams.

Lead design, build, and commission in-house test rigs and fixtures for humanoid robot subsystems and full robots. Define validation scope with system owners, specify and source test equipment, manage vendors and budgets, implement mechanical and electrical designs, and support long-term reliability, certification, and data acquisition for validation programs.

Lead and own the Services Business Process Automation program including SLM platform, BI reporting, and IT/OT integrations. Define roadmap, manage cross-functional deployments end-to-end, govern risks and budgets, measure adoption and SLAs, manage vendors, and translate technical work into executive narratives.

Lead design and delivery of end-to-end learned navigation and behavior systems for humanoid robots, build VLA/VLM-based multimodal navigation, design data pipelines and evaluation frameworks, and productionize large-scale ML models for reliable deployment on physical hardware in dynamic, multi-agent environments.