About this role · Stem
About the Role What if your deep knowledge of machine learning, statistical inference, and data engineering could directly shape how the world's most advanced AI systems reason and problem-solve? We're looking for data scientists with advanced degrees to work alongside leading AI research labs — designing expert-level challenges, authoring rigorous solutions, and auditing AI-generated code to make models smarter, more accurate, and more reliable. This is a fully remote, flexible contract role. No prior AI industry experience required — just serious domain expertise and a sharp analytical mind. - Organization: Alignerr - Type: Hourly Contract - Location: Remote - Commitment: 10–40 hours/week What You'll Do - Design Advanced Challenges — Create complex, domain-spanning data science problems covering hyperparameter optimization, Bayesian inference, cross-validation strategies, dimensionality reduction, and more - Author Ground-Truth Solutions — Develop rigorous, step-by-step technical solutions including Python/R scripts, SQL queries, and mathematical derivations that serve as the gold standard for AI training - Audit AI-Generated Code — Evaluate model outputs using libraries like Scikit-Learn, PyTorch, and TensorFlow for technical accuracy, efficiency, and correctness - Refine AI Reasoning — Identify logical flaws such as data leakage, overfitting, or improper handling of imbalanced datasets and provide structured feedback to sharpen model thinking - Document Failure Modes — Probe advanced language models on topics like neural network architectures and data engineering pipelines, capturing and reporting every reasoning gap Who You Are - Pursuing or holding a Master's or PhD in Data Science, Statistics, Computer Science, or a quantitative field with a strong data analysis focus - Strong foundational knowledge across supervised/unsupervised learning, deep learning, big data technologies (Spark/Hadoop), or NLP - Able to communicate highly technical algorithmic and statistical concepts clearly and concisely in writing - Exceptionally detail-oriented when reviewing code syntax, mathematical notation, and the validity of statistical conclusions - Self-directed and comfortable working independently on an async schedule - No prior AI or data annotation experience required Nice to Have - Experience with data annotation, data quality assurance, or AI evaluation systems - Proficiency in production-level data science workflows — MLOps, CI/CD for models, or similar - Familiarity with model evaluation frameworks or benchmarking methodologies Why Join Us - Work directly on cutting-edge AI projects alongside world-leading research labs - Fully remote and async — work when and where it suits you - Freelance autonomy with meaningful, intellectually stimulating work - Direct, hands-on engagement with industry-leading large language models - Potential for ongoing contract renewals as new projects launch