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Job description
About the Role
Join a remote, flexible contract opportunity where your graduate-level background in machine learning, statistical inference, and data engineering helps refine how advanced AI systems solve complex problems. The work focuses on testing model reasoning, identifying weak points, and establishing high-quality benchmarks for data science tasks.
No previous experience in the AI industry is needed. What matters most is strong subject matter knowledge, analytical thinking, and the ability to work independently.
Role Snapshot
- Organization: Alignerr
- Engagement type: Hourly contract
- Work mode: Remote
- Expected commitment: 10–40 hours per week
Key Responsibilities
- Build challenging, domain-specific data science tasks covering topics such as hyperparameter tuning, Bayesian methods, cross-validation, dimensionality reduction, and related areas.
- Create authoritative solutions with clear technical steps, including Python or R code, SQL queries, and mathematical derivations that can be used as reference answers.
- Review AI-generated code using tools and frameworks such as Scikit-Learn, PyTorch, and TensorFlow, checking for correctness, efficiency, and technical soundness.
- Spot reasoning issues in model outputs, including data leakage, overfitting, and poor handling of imbalanced datasets, then provide structured feedback to improve model performance.
- Handle assigned work independently and complete tasks asynchronously on your own schedule.
Who This Role Suits
This opportunity is intended for candidates currently enrolled in or already holding a Master’s or PhD in Data Science, Statistics, Computer Science, or another closely related quantitative discipline.
It is especially well suited to people with strong foundations in supervised and unsupervised learning, deep learning, big data tools such as Spark and Hadoop, or natural language processing.
Applicants should be able to explain advanced statistical and algorithmic ideas clearly in writing, pay close attention to coding and mathematical details, and remain dependable while working without close supervision.
Nice to Have
- Experience in data annotation, quality assurance, or AI evaluation work.
- Exposure to practical machine learning operations, including MLOps or CI/CD for models.
- Familiarity with model interpretability, fairness, or robustness testing.
- Academic research experience or strong technical writing skills.
Why Join
- Work with leading AI research teams and advanced language models.
- Enjoy fully remote, flexible working hours.
- Benefit from freelance-style independence while doing technically meaningful work.
- Contribute to improving how AI applies data science at scale.
- Potential for continued assignments and contract renewal as new projects begin.
Additional Information
This is an hourly contract role with a fully remote setup. The expected weekly workload is 10 to 40 hours. No prior AI or data annotation background is required.