Who we are CellVoyant is a biotechnology company that predicts stem cell differentiation using live cell microscopy and artificial intelligence. We use this approach to optimise and unlock human cell manufacturing for research and therapeutics applications. We aim to understand and solve important health issues, make a long-lasting positive impact on society and change the world. We spun out from the Carazo Salas lab at the University of Bristol in 2022 and are backed by venture capital firms who were the earliest investors in DeepMind, Exscientia, Recursion, Wayve, and Abcam. What we’re building At the heart of CellVoyant is FateView™️, our AI-powered SaaS platform. FateView™, enables biologists to visualize, track, and forecast cell differentiation in real-time. It supports high-throughput experimentation and model inference, combining microscopy, computer vision, cloud infrastructure, and AI to serve cutting-edge stem cell research and manufacturing. We are now looking for a DevOps / MLOps Engineer to join our growing technical team and help us scale FateView across cloud infrastructure, GPU-accelerated inference, and data pipelines. What you’ll do Play a key role in the development and maintenance of the FateView SaaS platform, which serves AI- and computer vision-powered workflows to end users in the life sciences. Work as a core member of the computational team (including ML scientists, data engineers, and software developers), while collaborating with the biology team, which generates microscopy data and designs stem cell differentiation protocols. Build and maintain GPU-enabled infrastructure to support both training and real-time inference pipelines for deep learning models. Deploy and orchestrate ML pipelines using Docker, Kubernetes, and tools like Kubeflow or Ray. Design, document, and deploy robust APIs to serve model predictions and data access to internal and external users. Implement secure authentication and authorization flows for platform users, in collaboration with the product and software teams. Administer and evolve our cloud platform, ensuring availability, security, and compliance with relevant regulations (e.g., GDPR, HIPAA readiness). Develop and maintain CI/CD pipelines to automate model training, testing, and deployment workflows. Support the team in troubleshooting, monitoring, and continuously improving the performance of data and inference pipelines in production. Requirements 5 years of experience, ideally in a DevOps, SRE, MLOps, or Data Engineering role. Proven experience with cloud platforms such as GCP, AWS, or Azure, with a strong preference for GCP. Strong understanding of Terraform and infrastructure-as-code best practices. Deep experience with Kubernetes, including cluster setup, node pool configuration, and workload orchestration. Experience deploying ML workloads on GPU clusters using tools like Kubernetes, Docker, Kubeflow, or Ray - especially for computer vision applications. Proficiency in Python and working with SQL databases. Solid grasp of machine learning lifecycle concepts, from data collection and preprocessing to training and inference. Ability to process and transform large-scale datasets (e.g., converting JSON to CSV, database ingestion, managing bottlenecks). Excellent communication and documentation skills, with the ability to clearly and concisely explain complex systems. Intellectual curiosity and a desire to stay up to date with the latest developments in cloud infrastructure, data engineering, and AI/ML tooling. Proven experience leading infrastructure or architecture efforts — especially in greenfield or early-stage environments. Nice to have Previous experience working on a SaaS platform in a biotech, healthcare, or life sciences setting. Hands-on experience with real-time ML inference and model monitoring in production. Familiarity with computer vision deep leading models Familiarity with data privacy, GDPR compliance Familiarity with scientific data formats (e.g., TIFF, OME-TIFF). Experience working in a seed-stage or Series A startup environment. Benefits Competitive salary and benefits package. Opportunities for professional development and career advancement. A collaborative and innovative work environment at the forefront of AI-powered biotech research. The chance to make a significant impact on the treatment of medical disorders through cutting-edge science and technology. Why join us You’ll be joining a fast-growing, interdisciplinary team that values autonomy, impact, and collaboration. We're tackling some of the hardest problems at the intersection of biology, AI, and cloud infrastructure —and your work will directly accelerate scientific discovery and therapeutic development. You’ll have the opportunity to shape core infrastructure decisions and grow alongside a company entering a key scaling phase.