Description du poste
About The Role
What if your deep knowledge of machine learning and statistics could directly shape how the world's most advanced AI systems think and reason? We're looking for Data Science Experts to stress-test, evaluate, and improve cutting-edge AI models --- exposing their blind spots, correcting their reasoning, and setting the gold standard for technical accuracy.
This is a fully remote, flexible contract role built for experienced data scientists and quantitative researchers who want meaningful, intellectually stimulating work on their own schedule.
- Organization: Alignerr
- Type: Hourly Contract
- Location: Remote
- Commitment: 10--40 hours/week
What You'll Do
- Design Advanced Challenges --- Craft complex, domain-spanning data science problems covering hyperparameter optimization, Bayesian inference, cross-validation strategies, dimensionality reduction, and more
- Author Gold-Standard Solutions --- Develop rigorous, step-by-step technical solutions including Python/R scripts, SQL queries, and mathematical derivations that serve as definitive reference answers
- Audit AI-Generated Code --- Evaluate model outputs using libraries like Scikit-Learn, PyTorch, and TensorFlow for correctness, efficiency, and best practices
- Refine Model Reasoning --- Identify logical failures such as data leakage, overfitting, and improper handling of imbalanced datasets, then provide structured feedback that directly improves how AI models think
- Document Failure Modes --- Systematically record where and how AI reasoning breaks down to help research teams harden model performance
Who You Are
- Holds or is pursuing a Master's or PhD in Data Science, Statistics, Computer Science, or a related quantitative field
- Strong foundational expertise in supervised and unsupervised learning, deep learning, statistical inference, or big data technologies (Spark, Hadoop)
- Able to communicate complex algorithmic concepts and statistical results clearly in writing
- Exceptionally detail-oriented --- you catch errors in code syntax, mathematical notation, and statistical conclusions that others miss
- Self-directed and comfortable working asynchronously on independent tasks
- No prior AI or annotation experience required
Nice to Have
- Experience with data annotation, data quality evaluation, or AI evaluation pipelines
- Familiarity with production-level data science workflows including MLOps or CI/CD for models
- Background in NLP, computer vision, or time-series analysis
Why Join Us
- Work directly with industry-leading AI research labs on cutting-edge model development
- Fully remote and flexible --- set your own hours and work from anywhere
- Freelance autonomy with the substance of high-impact, technically demanding work
- Engage with the most advanced language models in existence and influence their development
- Potential for ongoing work and contract extension as new projects launch