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- Tasks: Design and operate scalable multi-GPU infrastructure for cutting-edge AI and robotics.
- Company: Join Humanoid, the UK's pioneering AI and robotics company.
- Benefits: Competitive salary, stock options, paid vacation, and office perks.
- Other info: Enjoy a startup culture with opportunities for travel and collaboration.
- Why this job: Be at the forefront of AI innovation and make a real impact.
- Qualifications: 5+ years in DevOps/MLOps, strong Kubernetes and cloud experience required.
The predicted salary is between 70000 - 90000 £ per year.
Humanoid is the first AI and robotics company in the UK, creating the world’s most advanced, reliable, commercially scalable, and safe humanoid robots. Our first humanoid robot HMND 01 is a next-gen labour automation unit, providing highly efficient services across various use cases, starting with industrial applications.
Our Mission
At Humanoid we strive to create the world’s leading, commercially scalable, safe, and advanced humanoid robots that seamlessly integrate into daily life and amplify human capacity. We are building large-scale compute infrastructure for training next-generation robotics models, including transformer-based systems like VLA. This role focuses on designing and operating multi-GPU, cross-cloud platforms that enable efficient, reliable, and scalable model training. You’ll work at the intersection of DevOps, MLOps, and distributed systems, helping push the limits of real-world AI.
What You’ll Do:
- Design, build, and operate scalable multi-GPU infrastructure across cloud environments (AWS, GCP, etc.)
- Own the reliability, performance, and cost-efficiency of model training platforms
- Develop and maintain infrastructure-as-code and automation for provisioning, orchestration, and lifecycle management
- Build and evolve CI/CD pipelines for both infrastructure and ML training workflows
- Optimize distributed training workloads (scheduling, resource utilization, observability)
- Ensure high standards of reliability, scalability, security, and monitoring across systems
- Collaborate with ML engineers and researchers to enable efficient experimentation and productionization
- Troubleshoot complex issues across distributed systems, networking, and GPU workloads
- Define and implement best practices in DevOps/MLOps for a fast-scaling environment
- Document systems, architecture decisions, and operational processes
We’re Looking For:
- 5+ years of experience in DevOps, MLOps, or infrastructure engineering (Senior/Staff level)
- Strong experience with Kubernetes and containerized workloads at scale
- Proven experience with Infrastructure-as-Code (Terraform, Helm, or similar)
- Deep familiarity with at least one major cloud provider (AWS preferred)
- Solid experience building CI/CD systems (e.g., GitHub Actions, GitLab CI, ArgoCD)
- Proficiency in Python for automation and tooling
- Strong understanding of distributed systems, networking, and system reliability
- Ability to operate independently and drive large infrastructure initiatives
Nice to have:
- Hands-on experience with multi-GPU and/or distributed compute environments
- Experience with GPU scheduling/orchestration (e.g., Kubernetes schedulers - Volcano, Ray, etc.)
- Experience supporting ML workloads or training pipelines (PyTorch, TensorFlow, etc.)
- Experience with multi-cloud or hybrid cloud environments
- Background in performance optimization for training workloads
- Experience in robotics, simulation, or embodied AI systems
What we offer:
- Competitive salary plus participation in our Stock Option Plan
- Paid vacation with adjustments based on your location to comply with local labor laws
- Travel opportunities to our Vancouver and Boston offices
- Office perks: free breakfasts, lunches, snacks, and regular team events
- Freedom to influence the product and own key initiatives
- Collaboration with top‑tier engineers, researchers, and product experts in AI and robotics
- Startup culture prioritising speed, transparency, and minimal bureaucracy
Senior DevOps Engineer employer: Humanoid
Contact Detail:
Humanoid Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior DevOps Engineer
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect with people on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio or GitHub repository showcasing your projects, especially those related to DevOps and MLOps. This gives potential employers a taste of what you can do beyond your CV.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and soft skills. Practice common interview questions and scenarios related to distributed systems and cloud platforms. Confidence is key!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are genuinely interested in joining our mission at Humanoid.
We think you need these skills to ace Senior DevOps Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Senior DevOps Engineer role. Highlight your experience with Kubernetes, multi-GPU infrastructure, and any relevant cloud platforms. We want to see how your skills align with our mission at Humanoid!
Showcase Your Projects: Include specific projects that demonstrate your expertise in DevOps and MLOps. If you've built CI/CD pipelines or optimised distributed systems, let us know! Real-world examples help us understand your capabilities better.
Be Clear and Concise: When writing your application, keep it clear and to the point. Use bullet points for easy reading and make sure to highlight your key achievements. We appreciate straightforward communication!
Apply Through Our Website: Don’t forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for the role. We can’t wait to see what you bring to the table!
How to prepare for a job interview at Humanoid
✨Know Your Tech Inside Out
Make sure you’re well-versed in the technologies mentioned in the job description, especially Kubernetes, Infrastructure-as-Code tools like Terraform, and CI/CD systems. Brush up on your Python skills too, as you'll likely need to demonstrate your proficiency during the interview.
✨Showcase Your Problem-Solving Skills
Prepare to discuss specific challenges you've faced in previous roles, particularly around distributed systems and GPU workloads. Use the STAR method (Situation, Task, Action, Result) to structure your answers and highlight how you tackled complex issues effectively.
✨Understand Humanoid's Mission
Familiarise yourself with Humanoid’s mission and the role of AI in robotics. Be ready to discuss how your experience aligns with their goals of creating scalable and safe humanoid robots. This shows your genuine interest in the company and its vision.
✨Ask Insightful Questions
Prepare thoughtful questions about the team dynamics, ongoing projects, and the future direction of Humanoid. This not only demonstrates your enthusiasm but also helps you gauge if the company culture and values align with yours.