{"id":3181423,"url":"https://alion.io/job/cuspai-platform-engineer","title":"Platform Engineer","company":{"id":177783,"name":"CuspAI","domain":"cusp.ai","url":"https://alion.io/company/cuspai","size_band":"501-1000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Ashby","truth_index":{"grade":"A","score":88,"open_postings":6,"ghost_share":0,"stale_share":0.167,"repost_share":0.167,"time_to_fill_p50_days":74,"computed_at":"2026-10-31T05:58:55Z"}},"role":"DevOps","role_family":"DevOps","seniority":null,"employment_type":"full_time","work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Cambridge, United Kingdom","Amsterdam, Netherlands","Berlin, Germany","London, United Kingdom"],"countries":["GB","NL","DE"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":66000,"max_usd":146000,"period":"year","method":"role_country_seniority_unknown","sample_n":215},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AWS","optional":false},{"name":"CI/CD","optional":false},{"name":"Configuration Management","optional":false},{"name":"GCP","optional":false},{"name":"GitOps","optional":false},{"name":"Go","optional":false},{"name":"Helm","optional":false},{"name":"JAX","optional":false},{"name":"Kubernetes","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"TensorFlow","optional":false},{"name":"Terraform","optional":false},{"name":"Flyte","optional":true},{"name":"HPC","optional":true},{"name":"KServe","optional":true},{"name":"SLURM","optional":true},{"name":"TorchServe","optional":true},{"name":"Triton","optional":true}],"status":"live","first_seen_at":"2026-10-23T18:18:44Z","employer_posted_date":"2026-10-23","last_verified_at":"2026-10-31T13:59:15Z","board_verified":true,"closed_at":null,"days_open":7,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":7},"description":"About CuspAI\nCuspAI is the frontier AI company on a mission to solve the breakthrough materials needed to power human progress. While nature took billions of years to perfect molecules, we are harnessing AI to unlock trillion-dollar materials breakthroughs in months, not millennia. Our founding team is the most cited in the world, comprised of world-class researchers in AI, chemistry and engineering.\nWe are working on some of the hardest and most important challenges including energy, clean water, the future of compute, and carbon capture, and this is just the start of what our 'search engine' for next-generation materials will unlock.\nWe invite you to be part of a diverse, innovative team at the intersection of AI and materials science, working to create impactful partnerships that drive innovation, scalability, and industry collaboration. This work matters. Your work matters.\nWe’re on the cusp of the on-demand materials era. Join us.\nThe Role\nAs we grow, we are seeking a Platform Engineer with strong Python coding, DevOps and cloud platform expertise to build and maintain the infrastructure that powers our ML research teams. You will be the architect of the systems that enable our researchers to train and deploy models at scale.\nYour Impact\nIn this role, you will build and maintain the ML infrastructure platform that empowers our AI researchers and materials scientists to conduct cutting-edge experiments.\nYou will help to build and maintain the entire ML operations stack - from cloud architecture to deployment pipelines - ensuring our research teams can focus on science while you handle the systems.\nYou will be part of a newly created team working with our VP ML Engineering, in which you will have the chance to help shape our entire ML infrastructure strategy and make a significant impact on our platform's architecture.\nWhat You Will Do\nBuild the ML Infrastructure Platform: Design and implement a cloud-native platform on Kubernetes that enables researchers to easily train, evaluate, and deploy models without worrying about infrastructure complexity.\n\nOwn the MLOps Stack: Implement and maintain CI/CD pipelines, model registries, experiment tracking systems, and deployment automation - the full lifecycle of ML operations.\n\nScale Distributed ML Model Training: Build infrastructure to support distributed training across many GPUs, implementing solutions for data pipelines, checkpointing, and resource optimisation.\n\nPlatform Reliability: Ensure 99.9% uptime for our ML platform through monitoring, alerting, and automated recovery systems. Be the guardian of infrastructure stability.\n\nConfiguration Management: Use Kapitan to manage complex multi-environment Kubernetes configurations and ensure consistent deployments across dev, staging, and production.\n\nCost Optimisation: Implement resource management strategies to optimise cloud spending and detect inefficient usage while maximising computational throughput for our research teams.\n\nDeveloper Experience: Create tools and abstractions that make it simple for researchers to go from experiment to production without deep infrastructure knowledge.\n\nInterdisciplinary Collaboration: Partner closely with ML Researchers, Chemists, Materials Scientists and Software Engineers to understand their needs, and to build the infrastructure for groundbreaking projects\n\nMust Have Skills and Qualifications\nYou are someone who gets excited about the opportunity to enable scientists to work on world changing challenges in this domain, with a personal interest in the potential applications of the technology that Cusp is building.\n\nYou’re a builder of tools and infrastructure who enjoys making life as easy as possible for the teams. As part of your interest in this area, you stay up to date with the latest relevant technologies, tools, and open source projects.\n\nYou are a seasoned engineer with deep expertise in building and maintaining ML infrastructure (not model development), ideally in start-up environments. We need you to be able to hit the ground running and work autonomously as a subject matter expert, providing input and guidance around best practice where appropriate.\n\nYou bring deep experience with ML workloads on Kubernetes and multi-cloud platforms (AWS, GCP, neoclouds).\n\nYou have strong Python and/or Go programming skills for infrastructure automation - not just scripting.\n\nExpert-level proficiency in Infrastructure as Code (IaC) using Terraform, Helm, Kapitan, and GitOps workflows.\n\nExperience operating distributed ML platforms for JAX and/or PyTorch (Tensorflow would be less relevant).\n\nYou will also need to have GPU infrastructure experience, specifically managing GPU clusters and performance optimisation\n\nPrevious experience as a Software Engineer before moving into DevOps / MLOps / ML Infrastructure, or at least writing code regularly (at work and/or in your spare time), as this should equip you with the kind of coding skills we’re looking for.\n\nBonus Points (But Not Critical)\nExperience using our tech stack (Flyte, Kapitan, Pants) or similar tools\n\nExperience with HPC environments and job schedulers (Slurm, PBS)\n\nKnowledge of ML serving infrastructure (Triton, TorchServe, KServe)\n\nFamiliarity with scientific computing workflows and data management\n\nExperience with multi-tenant ML platforms\n\nBackground in supporting research teams (understanding their unique needs vs. production ML)\n\nWhat We Offer\nA competitive salary: We value and reward impact and growth\n\nEquity in CuspAI: You have a stake in the success of the company\n\nTime off to stay fresh: 28 days holiday (DE, NL, UK) or 21 days holiday (JP, SG, US), in addition to local public holidays\n\n‘Gold Standard’ parental leave: 26 weeks (primary caregiver) and 12 weeks (secondary caregiver) at full pay - we look after you and your family while we work on the most important materials discovery problems together\n\nProfessional development budget: We invest in your career development so you can stay up to date with the latest industry knowledge or add to your skills to increase impact and growth\n\nSolve meaningful problems: See how your work has a direct impact on advancing materials science and solving sustainability and climate-related problems through the creation and application of bleeding-edge SOTA technology and revolutionary techniques\n\nTrue interdisciplinary teamwork: Be part of a deeply collaborative environment bridging AI research, computational chemistry, and experimental science - work with world-class researchers and engineers who enjoy sharing knowledge and supporting each other\n\nJoin us in shaping the future of materials with AI. Together, we can create groundbreaking solutions for a more sustainable world.\nCuspAI is an equal opportunities employer committed to building a diverse and inclusive workplace. We do not discriminate on the basis of sex, race, religion or belief, ethnic or national origin, disability, age, citizenship, marital, domestic or civil partnership status, sexual orientation, gender identity, pregnancy or related condition (including breastfeeding), veteran status, or any other basis protected by applicable law.\nWe actively encourage applications from all backgrounds and value the unique perspectives and contributions that diversity brings to our team.\nPlease let us know if you require any specific adjustments during or after the interview process. 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