C
Platform Engineer
Contract type
Ongoing
Work mode
Remote
Experience
3 years
Job description
Platform Engineer at CuspAI responsible for building and maintaining the ML infrastructure platform that powers AI research teams, including Kubernetes-based cloud architecture, MLOps pipelines, and distributed GPU training.
At a glance
- Employment
- Full-time
- Work mode
- Remote
- Languages
- English
What you'll do
- Design and implement a cloud-native platform on Kubernetes that enables researchers to easily train, evaluate, and deploy models without worrying about infrastructure complexity
- Implement and maintain CI/CD pipelines, model registries, experiment tracking systems, and deployment automation - the full lifecycle of ML operations
- Build infrastructure to support distributed training across many GPUs, implementing solutions for data pipelines, checkpointing, and resource optimisation
- Ensure 99.9% uptime for the ML platform through monitoring, alerting, and automated recovery systems
- Use Kapitan to manage complex multi-environment Kubernetes configurations and ensure consistent deployments across dev, staging, and production
- Implement resource management strategies to optimise cloud spending and detect inefficient usage while maximising computational throughput
- Create tools and abstractions that make it simple for researchers to go from experiment to production without deep infrastructure knowledge
- Partner closely with ML Researchers, Chemists, Materials Scientists and Software Engineers to understand their needs and build infrastructure for groundbreaking projects
What we're looking for
- Gets excited about enabling scientists to work on world changing challenges, with a personal interest in the potential applications of the technology Cusp is building
- Builder of tools and infrastructure who enjoys making life as easy as possible for teams and stays up to date with the latest relevant technologies, tools, and open source projects
- Seasoned engineer with deep expertise in building and maintaining ML infrastructure (not model development), ideally in start-up environments; able to hit the ground running and work autonomously as a subject matter expert
- Deep experience with ML workloads on Kubernetes and multi-cloud platforms (AWS, GCP, neoclouds)
- Strong Python and/or Go programming skills for infrastructure automation - not just scripting
- Expert-level proficiency in Infrastructure as Code (IaC) using Terraform, Helm, Kapitan, and GitOps workflows
- Experience operating distributed ML platforms for JAX and/or PyTorch (Tensorflow would be less relevant)
- GPU infrastructure experience, specifically managing GPU clusters and performance optimisation
- Previous experience as a Software Engineer before moving into DevOps / MLOps / ML Infrastructure, or at least writing code regularly (at work and/or in spare time)
Nice to have
- Experience using Flyte, Kapitan, Pants or similar tools
- Experience with HPC environments and job schedulers (Slurm, PBS)
- Knowledge of ML serving infrastructure (Triton, TorchServe, KServe)
- Familiarity with scientific computing workflows and data management
- Experience with multi-tenant ML platforms
- Background in supporting research teams (understanding their unique needs vs. production ML)
Your team
ML Engineering
A newly created team working with the VP ML Engineering
Benefits
- A competitive salary
- Equity in CuspAI
- 28 days holiday (DE, NL, UK) or 21 days holiday (JP, SG, US), in addition to local public holidays
- 'Gold Standard' parental leave: 26 weeks (primary caregiver) and 12 weeks (secondary caregiver) at full pay
- Professional development budget
- Solve meaningful problems with direct impact on advancing materials science and sustainability
- True interdisciplinary teamwork bridging AI research, computational chemistry, and experimental science
Apply
Direct apply at Cuspai
Opens the job posting at Cuspai
About CuspAI
The frontier AI company on a mission to solve the breakthrough materials needed to power human progress
CuspAI is a frontier AI company building a 'search engine' for next-generation materials, working on challenges including energy, clean water, the future of compute, and carbon capture. Its founding team is comprised of world-class researchers in AI, chemistry and engineering.
Mission
Harnessing AI to unlock trillion-dollar materials breakthroughs in months, not millennia
Key facts
- AI / materials science
- Founding team is the most cited in the world, comprised of world-class researchers in AI, chemistry and engineering
- Working on energy, clean water, the future of compute, and carbon capture
What they value
- Diverse and inclusive workplace
- Collaboration
- Impact