ML Operations Engineer

CellVoyant; Bristol; On-site; GBP 60,000 - 90,000; Full time

Job summary

CellVoyant, a forward-thinking biotechnology company, seeks a DevOps / MLOps Engineer to enhance our AI-powered FateView platform. This pivotal role involves developing robust cloud infrastructure and efficiently managing machine learning pipelines, while collaborating closely with computational and biology teams. Join us to impact cutting-edge stem cell research and therapeutic applications.

Benefits

Competitive salary and benefits package

Opportunities for professional development

Collaborative and innovative work environment

Qualifications

• 5+ years of experience in DevOps, MLOps, or Data Engineering.
• Deep experience with Kubernetes and cloud platforms.
• Proficiency in Python and SQL databases.

Responsibilities

• Develop and maintain the FateView SaaS platform.
• Build and maintain GPU-enabled infrastructure.
• Administer cloud platform ensuring availability and compliance.

Skills

Python

Kubernetes

Cloud Platforms

Machine Learning Lifecycle Concepts

Data Transformation

Tools

Docker

Ray

Kubeflow

Terraform

Job description

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 isFateView️, 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 aDevOps / MLOps Engineerto 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 theFateView SaaS platform, which serves AI- and computer vision-powered workflows to end users in the life sciences.
• Work as a core member of thecomputational team(including ML scientists, data engineers, and software developers), while collaborating with thebiology team, which generates microscopy data and designs stem cell differentiation protocols.
• Build and maintainGPU-enabled infrastructureto support bothtraining and real-time inferencepipelines for deep learning models.
• Deploy and orchestrateML pipelinesusingDocker,Kubernetes, and tools likeKubefloworRay.
• Design, document, and deploy robustAPIsto serve model predictions and data access to internal and external users.
• Implement secureauthenticationandauthorization flowsfor platform users, in collaboration with the product and software teams.
• Administer and evolveour cloud platform, ensuringavailability,security, andcompliancewith relevant regulations (e.g., GDPR, HIPAA readiness).
• Develop and maintainCI/CD pipelinesto automate model training, testing, and deployment workflows.
• Support the team introubleshooting,monitoring, and continuously improving the performance of data and inference pipelines in production.

• 5+ years of experience, ideally in aDevOps, SRE, MLOps, or Data Engineeringrole.
• Proven experience with cloud platforms such asGCP,AWS, orAzure, with a strong preference forGCP.
• Strong understanding ofTerraformand infrastructure-as-code best practices.
• Deep experience withKubernetes, including cluster setup, node pool configuration, and workload orchestration.
• Experience deploying ML workloads onGPU clustersusing tools likeKubernetes,Docker,Kubeflow, orRay- especially for computer vision applications.
• Proficiency inPythonand working withSQLdatabases.
• Solid grasp ofmachine 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 aSaaS platformin abiotech, healthcare, or life sciencessetting.
• Hands-on experience withreal-time ML inferenceandmodel monitoringin production.
• Familiarity withcomputer vision deep leading models
• Familiarity withdata privacy,GDPR compliance
• Familiarity withscientific data formats(e.g., TIFF, OME-TIFF).
• Experience working in aseed-stageorSeries A startupenvironment.

• 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 ofbiology,AI, andcloud 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.