[Remote] Machine Learning Engineer, Integrity

Note: The job is a remote job and is open to candidates in USA. HackerRank is a company that helps enterprises like NVIDIA, Amazon, and Microsoft hire and upskill developers based on skills. They are seeking a Machine Learning Engineer focused on integrity to standardize model quality across integrity signals and drive strategy-level decisions in the development of new signals.ResponsibilitiesStandardize how model quality is defined, measured, and reported across all integrity signalsBuild the evaluation infrastructure, golden datasets, and benchmarking pipelines that give us and our customers genuine confidence in what we shipOwn the performance improvement strategy for each signalExplore newer architectures, emerging research, and different training paradigmsDefine the ML strategy for new signals from scratch: audio analysis, gaze tracking, behavioral anomaliesContinuously monitor how assessment fraud tooling is evolvingEvaluate new models as they emergeKnow when to abandon a strategy that is no longer moving the needleSystematically surface edge cases, build training data around them, and turn every customer-reported failure into a model that is harder to foolDrive strategy-level decisions: which new signals to build, whether to use models at all, and what the evidence saysSkillsYou have shipped ML systems in production that real users and real businesses depend onYou have deep intuition for where precision leaks happen and how to find them systematically, not by luckYou think in systems. A signal's accuracy number, its data pipeline, its serving infrastructure, and its customer-facing outcome are one problem to youYou care as much about evaluation methodology as model performance. You know that a metric measured wrong is worse than no metricYou are genuinely curious about adversarial dynamics. The fact that your model will be attacked is interesting to you, not exhaustingStandardize how model quality is defined, measured, and reported across all integrity signalsBuild the evaluation infrastructure, golden datasets, and benchmarking pipelines that give us and our customers genuine confidence in what we shipOwn the performance improvement strategy for each signal. Explore newer architectures, emerging research, and different training paradigmsDefine the ML strategy for new signals from scratch: audio analysis, gaze tracking, behavioral anomaliesContinuously monitor how assessment fraud tooling is evolving. Evaluate new models as they emergeSystematically surface edge cases, build training data around them, and turn every customer-reported failure into a model that is harder to foolDrive strategy-level decisions: which new signals to build, whether to use models at all, and what the evidence saysExperience with multimodal systems in production: vision, audio, or behavioral signal pipelinesBackground in adversarial ML or fraud/anomaly detectionPublications or open-source work in detection, robustness, or model evaluationPrior experience defining what production-ready means for a new signal category from scratchCompany OverviewHackerRank provides a platform that helps companies to evaluate technical skills and create opportunities. It was founded in 2009, and is headquartered in Mountain View, California, USA, with a workforce of 201-500 employees. Its website is http://hackerrank.com.Company H1B SponsorshipHackerRank has a track record of offering H1B sponsorships, with 1 in 2020. Please note that this does not guarantee sponsorship for this specific role.