HackerRank
Technology
AIResearcher
Neural analysis suggests this role is
optimal for Mid+ candidates.
“AI Researcher at HackerRank. Skills: Research methodology, ML model evaluation, Algorithmic fairness. Design research studies. Define 'good performance'”
Industry & Context.
Structure research question; Identify data; Execute to conclusion
What They're Looking For.
Must Have
Master's or PhD, Design methodology from scratch, Digitally self-sufficient, Write own scripts, Scrape data, Run own analyses, Think about fairness
Nice to Have
Familiarity with psychometric frameworks, IRT or educational assessment standards, Published work or thesis research, Algorithmic fairness experience, Evaluation design experience, Human judgment in AI systems experience, Experience running user research, Qualitative studies experience, Quantitative modeling experience, Prior B2B or enterprise product experience
What You'll Do.
Design research studies
Define 'good performance'
Build annotation frameworks
Build ground truth labels
Own bias audit process
Identify evaluation system bias
Understand bias reasons
Recommend bias changes
Conduct customer interviews
Conduct industry interviews
Understand skilled performance definition
Translate signals into constructs
Maintain documentation
Stay current on literature
Bring applicable ideas
How You'll Work.
Team & Collaboration
Product teams; ML teams; Commercial teams
Communication Scope
Communicate findings; Make methodology legible
Full Job Description
HackerRank helps companies like NVIDIA, Amazon, and Microsoft hire and upskill the next generation of developers based on skills, not pedigree. Our platform is trusted by over 2,500 of the world’s most innovative companies to build strong engineering teams ready for what’s next. Software has entered an era where humans and AI build side by side. As this shift accelerates, the definition of strong technical talent is changing. We give companies better ways to identify and invest in next-generation skills. People at HackerRank care deeply about the impact of their work and sweat the small details so our customers can be wildly successful with products they genuinely love to use. We move with urgency and believe great outcomes come from high standards. About the role How do you know if a candidate is doing well when there is no right answer? For twenty years, code evaluation was deterministic. A solution passed a test case or it did not. That world is over. Candidates today work alongside AI assistants, engage in multi-turn conversations, and produce outputs that blend human and machine reasoning. The evaluation signal is now qualitative, contextual, and deeply subjective. What Goldman Sachs considers a strong candidate looks different from what a Series B startup considers one. What looks like a correct answer in a Python interview looks different when a transcript is in the mix. And without a rigorous methodology for defining "good," any evaluation system we build risks embedding bias we cannot see and cannot defend. This role exists to solve that. Not as a support function. As the foundational research layer that everything else depends on. What you will do Design and execute research studies to define what "good performance" means across different job contexts, industries, and candidate types. Build the datasets, annotation frameworks, and ground truth labels that ML models on the Evaluation team learn from. Own the bias audit process: identify where our evaluation
Applying for this AI Researcher role?
Most applicants get filtered before a human reads their resume. See if yours makes the cut.
How to Apply on Greenhouse
- Create a Greenhouse profile before applying — it saves time across multiple applications.
- Upload your resume as a PDF; the parser handles it better than Word.
- Answer all knockout questions carefully — wrong answers auto-reject before a human sees you.
- Enable email notifications to track application status in real time.
ANONYMOUS · UNFILTERED
What do employees actually say about HackerRank?
Real rants from real employees. Read before you apply.