Senior Dev/ML Ops Engineer

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.

We're hiring a Senior Dev/MLOps Engineer to join our Data & Compute Platform team based in London.

Own and manage the full lifecycle of both ML models and core infrastructure

• from development and deployment to monitoring and continuous improvement.
• Build and maintain robust CI/CD pipelines for both software and ML workflows.
• Ensure reliability, scalability, observability, and security of production systems and ML infrastructure.
• Automate deployment, orchestration, and environment management using modern DevOps tooling.
• Collaborate closely with software engineers, data scientists, and product teams to bring ML-powered features to production.
• Proactively detect, troubleshoot, and resolve infrastructure and model performance issues.
• Stay up to date with industry best practices in DevOps, MLOps, and infrastructure engineering.
• Document infrastructure, workflows, and operational procedures clearly and thoroughly.

Proven experience in a senior-level DevOps, MLOps, or related infrastructure-focused engineering role.

• Strong proficiency in Python and familiarity with ML frameworks such as TensorFlow or PyTorch.
• Deep experience with cloud platforms (AWS, GCP, or Azure) and container orchestration tools (Docker, Kubernetes).
• Solid understanding of CI/CD systems (e.g., GitHub Actions, GitLab CI, ArgoCD) and infrastructure-as-code tools (e.g., Terraform, Helm).
• Familiarity with data engineering concepts such as ETL pipelines, data lakes, and large-scale batch/stream processing.
• Ability to design scalable, secure, and observable systems in fast-moving environments.
• Strong debugging and problem-solving skills across distributed systems.
• Excellent collaboration and communication skills, with experience working in cross-functional teams.
• Understanding of security and compliance best practices for both software and ML systems.

Meaningful time off to rest and recharge: 23 days of annual leave (accrued), 15 days of paid sick leave, and paid company holidays.

• Fully funded private healthcare for UK employees, with broad provider access, virtual and in‑person care, and strong mental health and serious illness support.
• Equity included–we believe builders should share in what they build.
• Pension scheme with a total 8% contribution (5% employee, 3% employer) on full earnings.
• Free daily breakfast, catered lunch, and snacks in‑office.
• Collaboration with top‑tier engineers, researchers, and product experts in AI and robotics.
• Freedom to influence the product and own key initiatives.

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