Top Tech Jobs & Startup Jobs in London

Build practical machine learning, statistical, and data science systems for Prolific’s participant marketplace. The role focuses on modeling participant supply, demand, and quality; improving matching to studies; validating useful signals; designing experiments and metrics; and deploying production-ready solutions. The scientist will independently shape ambiguous problems, select appropriate approaches ranging from classical statistics to LLMs, and collaborate with product, engineering, and Supply Data Science specialists.

Provides senior technical leadership for an engineering team by shaping technical direction, architecture, roadmaps, and engineering standards. Leads technical discovery and solution design, drives code quality, testing, reliability, and performance, and collaborates across teams. Mentors engineers, influences technical decisions, and connects engineering work to customer and business outcomes while contributing hands-on.

Lead Cloud Platform and SRE teams, guiding infrastructure strategy, Kubernetes operations, platform reliability, developer tooling, and technical growth. Own SLOs, SLAs, error budgets, observability, incident remediation, and secure cloud environments. Drive self-service infrastructure, GitOps, infrastructure-as-code, and platform adoption while balancing stability with developer velocity. Partner cross-functionally to communicate technical decisions and build scalable, resilient systems.

Conduct independent AI research focused on evaluation methodologies, alignment techniques, and synthetic data generation. Design rigorous experiments and scalable frameworks for evaluating LLMs and agent systems using human data. Build research infrastructure and practical tools, applying fine-tuning, optimization, quantization, adapters, and distillation. Publish research, contribute to open source, collaborate with engineering and product teams, mentor colleagues, and communicate complex AI concepts clearly.

Own analytics across the participant lifecycle to support acquisition, onboarding, activation, engagement, quality, retention and reactivation. Build metrics, dashboards, and experimentation frameworks with SQL and Python; partner with Product, Operations, Growth, and Data Science to run experiments and translate marketplace data into actionable decisions that improve participant health and supply sustainability.

Manage and optimise GKE Kubernetes clusters using Terraform; implement GitOps (ArgoCD) and developer golden paths; build infrastructure for safe, scalable deployments; support cloud compliance (SOC2, ISO-27001, Cyber Essentials); produce developer-facing documentation; act as GCP/Kubernetes technical lead and participate in on-call rotation.

Design, build, and maintain scalable data pipelines and platform services to support analytics, ML, and product teams. Implement infrastructure-as-code (Terraform) and Kubernetes-based deployments, develop data services/APIs, and ensure data quality, observability, security, and compliance. Partner with cross-functional teams, document systems, and continuously improve performance and reliability.

Own end-to-end product-led growth (PLG) for Prolific's self-serve B2B SaaS customers: drive acquisition, activation, engagement and retention across paid and organic channels, build onboarding and lifecycle programs, define PQLs, optimize paid strategy, partner with Product/Sales/RevOps/CS, and run experimentation to improve funnel metrics.

Define and build quality frameworks for human data programs, partner with clients and engineering to design evaluation, recruitment and annotation strategies, implement automated checks and dashboards, investigate data integrity, and upskill teams to deliver high-quality human data at scale.

Lead and mentor cross-functional engineering teams to deliver scalable, resilient cloud-native systems. Partner with product to define technical solutions, manage technical debt, hire and grow engineers, and drive engineering best practices. Hands-on leadership with strong frontend and distributed systems experience.