Remote Data Science Expert for AI Content & Evaluation

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

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.