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 Alpha - our rapidly developed humanoid platform now running in real industrial pilots - 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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