Data Scientist – AI Model Training & Evaluation
Company: Alignerr
Location: Atlanta, GA (Remote)
Type: Full-time
Remote: Yes
Posted: 2026-05-04
About this role
About The Role
We're looking for data scientists based in Germany to help train, evaluate, and improve next-generation AI systems. Your quantitative expertise will directly influence how state-of-the-art AI models reason, analyze, and communicate — making a real and lasting impact on the future of artificial intelligence.
- Organization: Alignerr
- Type: Hourly Contract
- Location: Remote
- Commitment: 10–40 hours/week
What You'll Do
- Evaluate AI model outputs for accuracy, reasoning quality, and statistical soundness
- Design and apply data-driven evaluation criteria and scoring rubrics
- Analyze patterns in AI-generated responses to identify systematic errors or biases
- Create high-quality training data including prompts, solutions, and annotations in your areas of expertise
- Provide structured, detailed feedback to improve model performance across data science and analytical tasks
- Review AI-generated code, visualizations, and statistical analyses for correctness
- Work independently and asynchronously on your own schedule
Who You Are
- Degree in Data Science, Statistics, Computer Science, Mathematics, or a related quantitative field (MS or PhD preferred)
- Strong foundation in statistics, probability, and machine learning concepts
- Proficient in Python, R, SQL, or similar data analysis tools
- Experienced with data wrangling, exploratory data analysis, and model evaluation
- Excellent analytical thinking with sharp attention to detail
- Strong written communication in English — able to explain complex technical concepts clearly and simply
- Self-motivated and comfortable working independently
Nice to Have
- Experience with deep learning frameworks such as PyTorch or TensorFlow
- Familiarity with NLP, large language models, or AI evaluation workflows
- Published research or industry experience in applied machine learning
- Background in A/B testing, causal inference, or experimental design
Why Join Us
- Work on cutting-edge...