AI Research Engineer-Field

Prolific is a company focused on reshaping the AI development landscape through human data infrastructure. They are seeking an AI Research Engineer to collaborate with AI labs and enterprise customers, advising on methodology and delivering research engagements to improve AI systems through high-quality human data.

Responsibilities:

• Serve as Prolific's technical research partner on customer engagements with AI labs and enterprise AI teams
• Advise and prototype bespoke solutions like evaluation methodology, rubric design, data collection approaches, quality frameworks, verifiers and validation frameworks, as well as RL environments
• Own methodology for projects - from scoping through delivery - working alongside our services team
• Build trusted relationships with customer research and engineering teams
• Surface patterns from customer work that should become platform capabilities, partnering with Product and Engineering to shape roadmap priorities
• Work with Services and Account teams to qualify opportunities and shape proposals
• Share learnings across the Research Engineering function to strengthen our collective expertise
• Contribute to Prolific's research publications and external collaborations as opportunities arise
• Collaborate with product teams to translate research insights into practical applications
• Mentor team members on advanced AI concepts and emerging research
• Communicate complex technical concepts to diverse stakeholders

Requirements:

• 3+ years of experience in AI/ML research, research engineering, or applied ML
• Strong knowledge of LLM evaluation methodologies, data collection design, and human feedback approaches
• Experience designing AI-assisted or model-in-the-loop workflows - you think creatively about where AI can augment human judgment
• Track record of executing research or applied AI/ML projects with clear outcomes
• Can build quickly when needed - you're comfortable prototyping solutions and build your own tooling
• Strong communicator across contexts - you can hold your own with AI lab researchers, translate methodology into actionable recommendations for customers, and bring internal teams along on what matters and why
• Based in US, Canada, or Mexico (or able to work US timezone hours)
• Prior customer-facing or consulting experience is a plus but not required