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Prolific Logo Prolific · IT - Software Development

Senior MLOps Engineer

United Kingdom · Job Posted February 01, 2026
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Job Description

Prolific is not just another player in the AI space – we are the architects of the human data infrastructure that's reshaping the landscape of AI development. In a world where foundational AI technologies are increasingly commoditized, it's the quality and diversity of human-generated data that truly differentiates products and models. The future of AI development relies on a critical, indispensable component: high-quality human data. Prolific provides the world's largest and most trusted source of this data to the teams pushing the boundaries of AI technology. As a Senior ML/LLMOps Engineer, you will be the backbone of our AI production lifecycle. You will bridge the gap between research and real-world application, ensuring our Data Scientists and AI Researchers have the high-performance infrastructure, automated pipelines, and deployment strategies needed to ship state-of-the-art models at scale. We deploy models and infrastructure responsible for a host of AI tasks, ranging from fraud detection to RAG based search.

Job Responsibility

  • Infrastructure & Platform Engineering: Design and maintain scalable cloud environments (GCP/AWS) using Terraform
  • Manage GPU/TPU resource allocation for training, fine-tuning, and interactive notebooks
  • Build internal services and CLI tools to streamline the developer experience for the AI team
  • ML & LLM Orchestration: Design CI/CD/CT (Continuous Training) pipelines using tools such as GitHub Actions, MLFlow, Vertex AI Pipelines
  • Develop reusable patterns for model serving
  • Managing service deployments to Kubernetes
  • Manage and optimize vector databases and embedding pipelines for RAG-based systems
  • Performance & Optimization: Implement techniques to reduce latency and increase throughput
  • Solve scaling bottlenecks for serverless or containerized model deployments
  • Optimize GPU utilization and cloud spend without compromising performance
  • Observability & Reliability: Monitor for model drift, data skew, and resource utilization
  • Implement LLM Tracing to monitor prompts, agent actions and general service health

Requirements

  • 5+ years experience with cloud infrastructure and infrastructure as code
  • Previous experience with the ML and LLM lifecycle - training, hosting, optimisation, observability
  • Used to working closely with researchers and data scientists - taking experiments from worksheets into production
  • Strong grasp of ML fundamentals and modern GenAI stack

What we offer

  • competitive salary
  • benefits
  • remote working
  • impactful, mission-driven culture
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