Jobs at Prolific

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 net-new and expansion enterprise sales cycles with frontier AI labs across the West. Build relationships with AI research, product, and executive stakeholders; manage complex, multi-threaded technical sales processes; develop proposals, pilots, and success plans with cross-functional teams; forecast pipeline and communicate deal health; and relay customer feedback to product and marketing. The role requires extensive experience selling strategic B2B technology solutions, including seven- and eight-figure deals.

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.

Lead and grow a product marketing function for Prolific's human data platform. Own positioning, messaging, launches, packaging, and go-to-market strategy; manage three PMMs; align Product, Sales, and vertical marketing; run market and competitive research and build sales enablement.

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.

Leads technical direction and delivery of scalable, secure software projects. Designs and implements solutions, collaborates with product stakeholders, drives coding standards and engineering excellence, mentors and supports engineers, contributes to hiring, influences technology adoption, and owns product and feature deployment and ongoing support.

Own the end-to-end PLG strategy for Prolific's self-serve funnel: drive acquisition, activation, engagement and retention. Develop and optimise onboarding, lifecycle and in-product messaging, referral programmes and paid acquisition across search, social and display. Improve organic growth via SEO and content, define PQLs, partner with Product, Sales, RevOps and CS, and lead data-driven experimentation to measure and optimise funnel performance.

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.

The Data Quality Engineer ensures the quality and integrity of data in studies, developing measurement systems, automation, and conducting analysis to uphold standards across projects.

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.

Design and own end-to-end data quality systems for managed AI data studies: define rubrics, sampling plans, automated checks, launch gates, drift detection, dashboards, and calibration. Investigate integrity issues, run root-cause analysis, build automation in Python/SQL, and partner with Product, Engineering, and Operations to embed quality controls, train reviewers, and scale repeatable quality playbooks across programs.

The Partner Growth Manager will build executive partnerships, drive revenue growth across the partner ecosystem, and represent Prolific at industry events, focusing on relationships in the US research and SaaS sectors.

In this role, you will recruit and engage specialized participants for AI projects, ensuring seamless collaboration with delivery teams and optimizing recruitment processes to meet client needs.

The Participant Recruitment Partner will identify and engage top-tier participants, manage client-specific recruitment operations, and enhance the participant pool quality through data-driven insights and collaboration.

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.

Lead Product Designer managing design vision and execution across multiple teams, enhancing user experiences within Prolific's marketplace and services.

Full‑stack product engineer working across Prolific domains to solve customer problems, build scalable web services, support production systems, respond to incidents, and collaborate directly with customers and cross-functional teams to deliver product-focused engineering solutions.

Senior Software Engineer contributing across the full stack within a product-focused, cross-functional team. Build, deploy, and support scalable cloud-native services using event-driven architectures, improve observability and test automation, collaborate with product and customers, and champion engineering best practices to deliver high-value features.

Build and support full-stack web applications in cross-functional teams using agile practices. Design, implement, and run production systems on cloud platforms with strong observability, testing, and event-driven patterns. Collaborate with product, design, and customers to continuously improve the product.