AI Research Engineer
AI in this role
Prolific
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 Role
Prolific AI Research (PAIR) is the AI research group at Prolific (https://labs.prolific.com/). We work on the science of evaluation: how to measure AI systems well, grounded in real human judgement at population scale. We are seeking a Research Engineer to conduct innovative research in key AI areas, including evaluation methodologies (particularly those grounded in human data), alignment techniques, and synthetic data generation. You'll bridge the gap between cutting-edge AI research and practical applications, helping to translate research insights into valuable products and services. As part of our commitment to contribute to the wider AI community, you'll be involved in writing papers that advance the field. Your work will directly impact how we understand, evaluate, and improve AI systems through high-quality human data.
What You’ll Be Doing
Research & Innovation
- Lead independent research projects in AI evaluation methodologies, alignment techniques, and synthetic data generation
- Design and implement novel evaluation frameworks for LLMs and agent systems that are grounded in human data
- Contribute to the academic AI community through publications and open-source contributions
- Stay at the forefront of AI research and pioneer innovative approaches to tackle pressing open challenges in the field
Technical Implementation
- Design and conduct rigorous experiments to study AI models and systems with sound methodological approaches
- Develop scalable frameworks for systematic evaluation of model behaviors and capabilities
- Create tools and frameworks that transform research insights into practical applications
- Build infrastructure to support large-scale research experiments when needed
- Apply knowledge of model fine-tuning, optimization techniques, distillation, and other ML engineering practices to support research goals
Cross-Functional Collaboration
- Work closely with ML engineers, data scientists, and product teams to translate research insights into practical applications
- Mentor team members on advanced AI concepts and emerging research directions
- Communicate complex technical concepts to diverse stakeholders
What You’ll Bring
- 5+ years of engineering experience with significant AI/ML focus
- Demonstrated research experience through publications, open-source contributions, or impactful projects
- Strong engineering fundamentals and experience implementing AI systems in production environments
- Deep knowledge of LLM evaluation methodologies, alignment techniques, and model optimization approaches
- Experience with model fine-tuning, adapters, quantization, and distillation frameworks
- Self-motivation and ability to define and pursue research directions independently
- Excellent understanding of current challenges in AI safety, reliability, and alignment
- Strong communication skills and ability to explain complex research concepts clearly
- Passion for staying current with the rapidly evolving AI research landscape
Why Prolific is a great place to work
We've built a unique platform that connects researchers and companies with a global pool of participants, enabling the collection of high-quality, ethically sourced human behavioral data and feedback. This data is the cornerstone of developing more accurate, nuanced, and aligned AI systems.
We believe that the next leap in AI capabilities won't come solely from scaling existing models but from integrating diverse human perspectives and behaviors into AI development. By providing this crucial human data infrastructure, Prolific is positioning itself at the forefront of the next wave of AI innovation—one that reflects the breadth and the best of humanity.
Working for us will place you at the forefront of AI innovation, providing access to our unique human data platform and opportunities for groundbreaking research. Join us to enjoy a competitive salary, benefits, and remote working within our impactful, mission-driven culture.
Links to more information on Prolific
Privacy Statement
By submitting your application, you agree that Prolific may collect your personal data for recruiting and global organization planning. Prolific's Candidate Privacy Notice explains what personal information Prolific may process, where Prolific may process your personal information, its purposes for processing your personal information, and the rights you can exercise over Prolific use of your personal information.
How we rate this
AI Research Engineer at Prolific rates 96 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.
Builds AI. The job is building AI systems.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.
Prepare for this job
A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.
Skills and AI tools this role asks for
Questions you could be asked
- Walk me through fine-tuning a model: what data did you use, and how did you check the result?
- How do you decide that one model's output is better than another's for a given task?
- How do you think about the risk of an AI system in this kind of role failing silently?
- Tell me about a research question you investigated. What did you find?
- How would you decide a model or AI system is ready to ship?
Adapt your resume
- List these exact terms on your resume: Fine Tuning, AI Evaluation, AI Safety, and AI Research. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
- Lead with what you built, trained or shipped — this role is judged on the AI system itself, not the tools around it.
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