What if your deep knowledge of machine learning, statistics, and data engineering could directly shape how the next generation of AI reasons through complex problems? We're looking for Data Science Experts to challenge, evaluate, and improve cutting-edge AI models — helping them think more rigorously, reason more accurately, and solve harder problems.
This is a fully remote, flexible contract role built for working data scientists, researchers, and quantitative professionals who want to apply their expertise in a high-impact, asynchronous environment.
Organization: Alignerr
Type: Hourly Contract
Location: Remote
Commitment: 10–40 hours/week
What You'll Do
Design Advanced Challenges — Create complex, domain-specific data science problems spanning hyperparameter optimization, Bayesian inference, cross-validation strategies, dimensionality reduction, and more
Author Ground-Truth Solutions — Develop rigorous, step-by-step reference solutions including Python/R scripts, SQL queries, and mathematical derivations that serve as the gold standard for AI evaluation
Audit AI-Generated Code — Evaluate AI outputs using libraries like Scikit-Learn, PyTorch, and TensorFlow for technical correctness, efficiency, and best practices
Sharpen AI Reasoning — Identify logical failures in AI-generated analysis — such as data leakage, overfitting, or mishandled class imbalance — and provide structured feedback that improves how models think and respond
Who You Are
Holds a Master's (pursuing or completed) or PhD in Data Science, Statistics, Computer Science, or a related quantitative field
Strong foundational expertise in areas such as supervised/unsupervised learning, deep learning, NLP, or big data technologies (Spark, Hadoop)
Able to communicate complex algorithmic and statistical concepts clearly in writing
Precise and detail-oriented when reviewing code syntax, mathematical notation, and statistical conclusions
Self-motivated and comfortable working independently in an async, task-based environment
No prior AI or annotation experience required
Nice to Have
Experience with data annotation, data quality, or AI evaluation workflows
Familiarity with production-level data science practices — MLOps, CI/CD for models, model monitoring
Background in technical writing, research, or academic publishing
Why Join Us
Work directly with industry-leading AI research labs on frontier model development
Fully remote and asynchronous — work when and where it suits you
Freelance autonomy with meaningful, intellectually stimulating work
Contribute to AI systems that will shape how data science is understood and applied at scale
Potential for ongoing contract renewals as new projects launch
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