Judah D.

Key Skills

Software

Other

Top Subject Matter

LLM evaluation and training data optimization

LLM evaluation

response grading

Top Data Types

Text

Top Task Types

Fine-tuning

Freelancer Overview

AI & Software Engineer. Brings 14+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Other. Education includes Bachelor of Science, MIT (2008) and Master of Science, MIT (2013). AI-training focus includes data types such as Text and labeling workflows including Evaluation, Rating, and Fine-tuning.

Labeling Experience

AI Training Specialist — Alignerr (2025–Present)

OtherText

Performed LLM output evaluation to assess quality, reasoning, and consistency against desired criteria. Optimized training datasets by analyzing model behavior and updating example selections and associated annotations. Helped improve training workflow reliability by identifying failure patterns such as low-quality responses and hallucinations. • Evaluated LLM responses for correctness and alignment • Improved dataset validation through iterative review • Supported model reasoning enhancements via targeted data updates • Reduced hallucination tendencies through quality-focused evaluation

2025 - Present

AI Data Analyst — Outlier AI (2023–Present)

OtherText

Conducted LLM evaluation and response grading to score outputs according to defined quality standards. Validated and ensured dataset integrity by checking label consistency and dataset suitability for training or evaluation. Contributed to more reliable AI performance by supporting structured grading and validation of model responses. • Performed response grading for LLM outputs • Supported dataset validation and consistency checks • Evaluated model performance using rubric-based assessment • Improved training/evaluation readiness through data QA

2023 - Present

AI & Software Engineer — Scale AI (2018–2024)

OtherTextFine-tuning

Enhanced AI workflows with a focus on reducing hallucinations and improving overall model reliability. Supported training-related optimization by refining processes and dataset usage to better align outputs with expected behavior. Contributed to improved model performance through iterative workflow and training optimization efforts. • Worked on hallucination reduction initiatives • Improved training/inference workflow processes • Assisted optimization of AI outputs through data-driven iteration • Supported reliability improvements for model behavior

2018 - 2024

Education

Work History