- Experience
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- Salary
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- Openings
- 1
- Posted
- 9 hours ago
Job description
About the role
This contract position is designed for Masters-level data scientists who want to help evaluate and improve advanced AI systems. The work centers on challenging model reasoning, uncovering weak spots, and strengthening technical accuracy across difficult data science tasks.
The engagement is fully remote and offers flexible scheduling. Previous experience in the AI industry is not required; what matters most is strong, rigorous knowledge of data science and a careful eye for correctness.
Engagement details
- Organization: Alignerr
- Contract type: Hourly
- Work mode: Remote
- Weekly commitment: 10 to 40 hours
Responsibilities
- Create advanced data science challenges that span topics such as hyperparameter tuning, Bayesian methods, cross-validation approaches, and dimensionality reduction.
- Develop authoritative solutions with clear, step-by-step reasoning, including Python or R code, SQL queries, and mathematical derivations that can serve as the reference answer.
- Review AI-generated code and technical outputs for accuracy, computational efficiency, and sound methodology using tools such as Scikit-Learn, PyTorch, and TensorFlow.
- Detect mistakes in model reasoning, including leakage, overfitting, and mishandling of imbalanced data, then provide structured feedback to improve future outputs.
- Complete assignments independently and asynchronously according to your own schedule.
Requirements
- Currently pursuing or already holding a Masters or PhD in Data Science, Statistics, Computer Science, or another strongly quantitative discipline.
- Solid grounding in core machine learning areas such as supervised learning, unsupervised learning, deep learning, NLP, or big data technologies like Spark and Hadoop.
- Ability to explain technical and statistical ideas clearly and precisely in writing.
- Strong attention to detail, with the ability to notice syntax issues, notation inconsistencies, and weak statistical conclusions.
- Comfort working independently and reliably without close supervision.
- No prior AI or data annotation experience is needed.
Preferred background
- Experience with data annotation, data quality processes, or evaluation frameworks.
- Exposure to practical data science operations such as MLOps, CI/CD for models, or model monitoring.
- Background in academic research, technical documentation, or peer review.
- Familiarity with applied machine learning areas such as computer vision, time series, or recommender systems.
Why join
- Contribute to advanced AI projects alongside leading research teams.
- Enjoy a fully remote setup with flexible working hours and location.
- Work with the independence of freelance-style engagement on meaningful, challenging tasks.
- Gain hands-on exposure to cutting-edge large language models.
- There is potential for continuing assignments and contract renewals as new work becomes available.
Additional information
This role is structured as an hourly contract and is remote. The expected workload is 10 to 40 hours per week.