Jobs at Prolific

Own and scale lifecycle marketing for a product-led, self-serve business across onboarding, activation, retention, reactivation, and expansion. Audit existing programs, define behavioral segments and PQL signals, launch email and in-app journeys, run experiments, analyze funnel and retention metrics, and document lifecycle processes. Partner with Product, Sales, RevOps, Customer Success, and Marketing during a three-month fixed-term contract.

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.

Build and maintain scalable dbt data models, pipelines, macros, tests, documentation, and semantic layers. Develop trustworthy LLM-powered data transformations and agentic workflows with evaluation, monitoring, governance, and human oversight. Maintain analytics infrastructure supporting BI and natural-language querying, translate technical concepts for stakeholders, mentor team members, and collaborate with product, engineering, and BI teams.

Own the end-to-end success lifecycle for strategic customers developing frontier AI models. Drive onboarding, adoption, consumption, expansion, renewals, advocacy, and value realization. Serve as a trusted advisor to executive, research, technical, and business stakeholders; lead business reviews, develop success plans, forecast consumption, mitigate risks, and coordinate cross-functional teams. Improve customer-success playbooks and represent customer outcomes through case studies and advocacy.

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.

Lead full-cycle talent acquisition for Prolific’s Product and Design teams. Partner with senior leaders to develop hiring strategies, source specialized and senior talent globally, manage candidates from outreach through offer, use hiring data and market insight to guide decisions, improve recruitment practices and technology, calibrate interviewers, and strengthen employer branding and diversity.

Manage and optimize production Kubernetes clusters on GKE using Terraform, build secure and scalable cloud infrastructure, and develop golden paths and self-service automation for developers. The role supports cloud compliance standards, provides technical expertise on GCP and Kubernetes, maintains infrastructure documentation and solutions, and participates in an on-call rotation. Experience with AWS, CDK, Datadog, and cloud security practices is advantageous.

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.

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.

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.

Senior Product Designer responsible for discovering and solving complex product problems, creating user journeys, wireframes, prototypes, and service maps, and validating designs through research and experimentation. The role collaborates with product and engineering teams, improves product experiences, contributes to design systems, and advocates for customer-centered, accessible design across the organization.

Build full-stack software solutions for frontier AI companies and enterprise customers. Translate customer and business problems into scalable products, collaborate with account managers and customers, work across shared codebases and technology domains, and support production systems and incident response. The role requires strong product judgment, rapid iteration, direct customer communication, and the ability to balance startup speed with reliable engineering.

Manage the operational delivery of human data for a strategic AI customer. Responsibilities include translating requirements into workflows, managing participant pools and onboarding, tracking supply and quality, leading cross-functional projects, resolving operational issues, documenting processes, and improving scalability with Product and Engineering. The role also supports participant assessment and certification programs while serving as an operational point of contact for delivery teams.

Own operational delivery for complex research customer projects, including participant acquisition, onboarding, verification, activation, quality monitoring, and supply development. Build project plans, workflows, playbooks, and scalable processes while optimizing participant funnels and operational metrics. Partner with product, data, science, and customer success teams to improve time-to-data, fill rates, participant quality, and customer outcomes across Prolific’s Research platform.

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 complex AI client projects from requirements gathering through delivery, serving as the primary client contact and coordinating Sales, Operations, Product, and Engineering. Responsibilities include defining scopes and delivery plans, managing risks, quality, timelines, budgets, profitability, and KPIs, resolving execution challenges, and improving scalable processes for AI project delivery.

Owns end-to-end human data operations for specialized participant pools supporting AI projects. Responsibilities include participant onboarding, verification, quality management, engagement metrics, process optimization, project planning, documentation, and stakeholder enablement. Partners with product, technology, data science, delivery, and customer success teams to scale manual workflows into technology-driven solutions and align participant capabilities with client-specific AI requirements.

Manage end-to-end operations for specialized participant pools supporting AI projects. Responsibilities include participant onboarding, verification, quality management, engagement monitoring, process optimization, project planning, documentation, and stakeholder enablement. Partner with product, technology, data, science, delivery, and customer success teams to scale manual workflows into technology-driven solutions and support high-quality human data collection for AI tasks.

Analyzes human-generated data quality across AI programs using SQL, Python, statistical methods, and hands-on annotation review. Investigates quality issues, identifies failure patterns, measures impact, and develops recommendations. Supports quality pipelines, automated validations, rubrics, gold sets, calibration exercises, reporting, and dashboards. Collaborates with quality engineering, operations, delivery, and engineering teams to improve annotation design, training, tooling, and quality controls.

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.