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Dan Binisan

Dan Binisan

Machine Learning Expert,AI Training & Evaluation Intern

USA flagnew york, Usa
$30.00/hrExpertScale AIAppen

Key Skills

Software

Scale AIScale AI
AppenAppen

Top Subject Matter

AI Model Evaluation and Training
NLP and Conversational AI
AI Content Evaluation

Top Data Types

TextText
ImageImage
DocumentDocument

Top Task Types

ClassificationClassification
SegmentationSegmentation
Question AnsweringQuestion Answering
Text SummarizationText Summarization
Evaluation/RatingEvaluation/Rating
Data CollectionData Collection
Computer Programming/CodingComputer Programming/Coding

Freelancer Overview

AI Training & Evaluation Intern. Brings 12+ years of professional experience across legal operations, contract review, compliance, and structured analysis. Core strengths include Scale AI, Appen, and Outlier AI. Education includes Bachelor of Science, University of California, Berkeley (2023) and Bachelor of Science, Stanford University (2020). AI-training focus includes data types such as Text and labeling workflows including Evaluation, Rating, and Classification.

ExpertEnglish

Labeling Experience

Scale AI

AI Training & Evaluation Intern

Scale AIText
As an AI Training & Evaluation Intern at Scale AI, I evaluated and scored AI-generated responses across benchmarks. I annotated large-scale datasets to support supervised and reinforcement learning workflows. I was involved in prompt testing and cross-functional collaboration to enhance AI model performance. • Evaluated and scored AI-generated outputs for reasoning, factuality, and coherence • Annotated datasets for supervised and RLHF workflows • Conducted prompt testing to optimize responses • Refined evaluation guidelines with team members

As an AI Training & Evaluation Intern at Scale AI, I evaluated and scored AI-generated responses across benchmarks. I annotated large-scale datasets to support supervised and reinforcement learning workflows. I was involved in prompt testing and cross-functional collaboration to enhance AI model performance. • Evaluated and scored AI-generated outputs for reasoning, factuality, and coherence • Annotated datasets for supervised and RLHF workflows • Conducted prompt testing to optimize responses • Refined evaluation guidelines with team members

2025 - Present

AI Content Analyst

Text
As an AI Content Analyst for Outlier AI, I reviewed and ranked AI-generated content using structured rubrics. I flagged misleading or poor-quality outputs to enhance dataset quality and reliability. I tested prompt variations and documented major performance differences. • Reviewed and scored AI-generated responses • Flagged biased or inaccurate outputs for correction • Tested different prompts for optimal model outputs • Maintained high annotation throughput with consistency

As an AI Content Analyst for Outlier AI, I reviewed and ranked AI-generated content using structured rubrics. I flagged misleading or poor-quality outputs to enhance dataset quality and reliability. I tested prompt variations and documented major performance differences. • Reviewed and scored AI-generated responses • Flagged biased or inaccurate outputs for correction • Tested different prompts for optimal model outputs • Maintained high annotation throughput with consistency

2024 - 2028
Appen

Machine Learning Data Annotator

AppenTextClassification
As a Machine Learning Data Annotator at Appen, I labeled and validated datasets for NLP and conversational AI systems. I applied strict annotation guidelines to generate high-quality data for model training. I performed quality checks and helped resolve any annotation inconsistencies. • Labeled text data for conversational AI and NLP • Validated and reviewed annotation output • Applied comprehensive guidelines for labeling • Contributed to improved model accuracy through quality data

As a Machine Learning Data Annotator at Appen, I labeled and validated datasets for NLP and conversational AI systems. I applied strict annotation guidelines to generate high-quality data for model training. I performed quality checks and helped resolve any annotation inconsistencies. • Labeled text data for conversational AI and NLP • Validated and reviewed annotation output • Applied comprehensive guidelines for labeling • Contributed to improved model accuracy through quality data

2024 - 2025

Education

U

University of California, Berkeley

Bachelor of Science, Electrical Engineering and Computer Sciences

Bachelor of Science
2020 - 2023
S

Stanford University

Bachelor of Science, Computer Science

Bachelor of Science
2017 - 2020

Work History

O

Optera AI

Senior Machine Learning Engineer

New York
2023 - Present
M

Mosaic Financial Technologies

Machine Learning Engineer II

San Francisco
2021 - 2023