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.

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  Own and manage the full lifecycle of both ML models and core infrastructure - from development and deployment to monitoring and continuous improvement.

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  Build and maintain robust CI/CD pipelines for both software and ML workflows.

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  Ensure reliability, scalability, observability, and security of production systems and ML infrastructure.

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  Automate deployment, orchestration, and environment management using modern DevOps tooling.

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  Collaborate closely with software engineers, data scientists, and product teams to bring ML-powered features to production.

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  Proactively detect, troubleshoot, and resolve infrastructure and model performance issues.

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  Stay up to date with industry best practices in DevOps, MLOps, and infrastructure engineering.

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  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.