Data Science Expert - AI Content Specialist

Alignerr Corp.; Melbourne; Remote; AUD 83,000 - 165,000; Part time

Benefits offered by this job

Job summary

Alignerr is seeking a Data Science Expert to shape AI training by designing expert challenges, writing gold-standard solutions, and auditing AI-generated code. This remote hourly contract role partners with leading AI labs, offering high-impact, independent work.

You will work on diverse ML topics, document failures, and help improve AI reasoning for real-world applications. Requires graduate-level data science expertise and ability to communicate complex concepts clearly.

Qualifications

• Pursuing or holding a Master's/PhD in DS, Statistics, CS, or related quantitative field.
• Strong foundation in supervised/unsupervised learning, deep learning, NLP, big data technologies (Spark, Hadoop), or statistical inference.
• Ability to clearly explain complex algorithms in writing.
• Exceptionally detail-oriented; can spot errors in code and notation.
• Self-directed; comfortable working independently on task-based work.
• No prior AI annotation experience required.

Responsibilities

• Design Expert Challenges spanning hyperparameter optimization, Bayesian inference, cross-validation strategies, dimensionality reduction, and more.
• Author ground-truth solutions with Python/R scripts, SQL queries, and mathematical derivations.
• Audit AI-generated code from libraries like Scikit-Learn, PyTorch, and TensorFlow for correctness and efficiency.
• Sharpen AI reasoning by identifying data leakage, overfitting, or imbalanced datasets and giving structured feedback.
• Document failure modes to harden AI systems against real-world misuse.

Job description

Data Science Expert - AI Content Specialist (AI Training)

About The Role

What if your deep knowledge of machine learning, statistics, and data engineering could directly shape how the world's most advanced AI thinks and reasons? We're looking for Data Science Experts to work alongside leading AI research labs - designing expert-level challenges, writing gold-standard solutions, and auditing AI-generated code to make AI smarter, more rigorous, and more reliable.

• Organization: Alignerr
• Type: Hourly Contract
• Location: Remote
• Commitment: 10-40 hours/week

What You'll Do

• Design Expert Challenges - Create advanced data science problems spanning hyperparameter optimization, Bayesian inference, cross-validation strategies, dimensionality reduction, and more - problems that genuinely stress-test AI reasoning
• Author Ground-Truth Solutions - Develop rigorous, step-by-step technical solutions including Python/R scripts, SQL queries, and mathematical derivations that serve as the definitive benchmark for AI responses
• Audit AI-Generated Code - Evaluate outputs from libraries like Scikit-Learn, PyTorch, and TensorFlow for correctness, efficiency, and best practices - catching what others miss
• Sharpen AI Reasoning - Identify logical failures in AI outputs - data leakage, overfitting, improper handling of imbalanced datasets - and provide structured feedback that improves how models think
• Document Failure Modes - Surface and articulate edge cases and reasoning gaps so AI systems can be hardened against real-world misuse

Who You Are

• Holds or is pursuing a Master's or PhD in Data Science, Statistics, Computer Science, or a related quantitative discipline
• Strong foundational expertise in core data science domains - supervised/unsupervised learning, deep learning, NLP, big data technologies (Spark, Hadoop), or statistical inference
• Able to communicate complex algorithmic and statistical concepts clearly and precisely in writing
• Exceptionally detail-oriented - you catch errors in code syntax, mathematical notation, and statistical interpretation
• Self-directed and comfortable working independently on task-based assignments
• No prior AI or annotation experience required - your domain expertise is what matters

Nice to Have

• Experience with data annotation, data quality, or model evaluation systems
• Familiarity with production-level data science workflows - MLOps, CI/CD for models, or model monitoring
• Prior work reviewing or auditing technical content at scale

Why Join Us

• Work directly with industry-leading large language models on problems that genuinely matter
• Fully remote and async - work when and where it suits you
• Freelance autonomy with the substance of high-impact, expert-level work
• Engage with a global network of top-tier researchers and technical contributors
• Potential for ongoing work and contract extension as new projects launch