Robisen Jimmy

Key Skills

Software

Lionbridge

Top Subject Matter

Llms Domain Expertise

Generative AI

Humanities Domain Expertise

Top Data Types

Text

Audio

Document

Top Task Types

Prompt Response Writing SFT

Classification

Freelancer Overview

Generative AI Specialist (Humanities). Brings 5+ years of professional experience across legal operations, contract review, compliance, and structured analysis. Core strengths include Internal, Proprietary Tooling, and Lionbridge. Education includes Doctor of Philosophy, University of Southern California (2023) and Master of Arts, Georgetown University (2022). AI-training focus includes data types such as Text and labeling workflows including Prompt + Response Writing (SFT), Evaluation, and Rating.

Labeling Experience

Generative AI Specialist (Humanities)

TextPrompt Response Writing SFT

As a Generative AI Specialist at Innodata, I wrote, edited, and refined prompts and responses to train and evaluate large language models. My responsibilities included evaluating and ranking AI-generated outputs using comparative and rubric-based methods, identifying safety, accuracy, and compliance issues. I authored and implemented detailed annotation guidelines and performed multilingual evaluation to ensure high-quality data labeling outcomes. • Adversarially tested model responses for logical errors, bias, hallucinations, and policy risks. • Applied and updated gold standard annotation protocols to maintain evaluation consistency. • Performed fact-checking and source verification during data labeling tasks. • Delivered high-volume, guideline-driven annotation and evaluation remotely.

As a Generative AI Specialist at Innodata, I wrote, edited, and refined prompts and responses to train and evaluate large language models. My responsibilities included evaluating and ranking AI-generated outputs using comparative and rubric-based methods, identifying safety, accuracy, and compliance issues. I authored and implemented detailed annotation guidelines and performed multilingual evaluation to ensure high-quality data labeling outcomes. • Adversarially tested model responses for logical errors, bias, hallucinations, and policy risks. • Applied and updated gold standard annotation protocols to maintain evaluation consistency. • Performed fact-checking and source verification during data labeling tasks. • Delivered high-volume, guideline-driven annotation and evaluation remotely.

2024 - Present

Senior Generative AI / NLP Scientist

Text

At Adobe as a Senior Generative AI / NLP Scientist, I evaluated AI-generated content for accuracy, safety, and compliance, contributing to model quality and reliability. I designed frameworks for human-in-the-loop evaluation, rubric scoring, and preference ranking of generative outputs. My work informed mitigation strategies for issues like bias, factual inconsistency, and brand guidelines. • Collaborated with teams to establish content evaluation protocols and enforce annotation standards. • Identified weakness patterns in output coherence and factual accuracy during evaluation. • Created and refined template-based evaluation tools for model assessment. • Participated in cross-functional audits to ensure annotation quality.

At Adobe as a Senior Generative AI / NLP Scientist, I evaluated AI-generated content for accuracy, safety, and compliance, contributing to model quality and reliability. I designed frameworks for human-in-the-loop evaluation, rubric scoring, and preference ranking of generative outputs. My work informed mitigation strategies for issues like bias, factual inconsistency, and brand guidelines. • Collaborated with teams to establish content evaluation protocols and enforce annotation standards. • Identified weakness patterns in output coherence and factual accuracy during evaluation. • Created and refined template-based evaluation tools for model assessment. • Participated in cross-functional audits to ensure annotation quality.

2022 - 2024

NLP / ML Engineer

Text

As an NLP / ML Engineer at Grammarly, I conducted evaluations of AI-generated rewrites, focusing on clarity, correctness, and appropriateness for diverse audiences. I carried out detailed audits, fact-checking, and guideline-driven quality assurance of long-form and short-form AI outputs. I improved rater agreement by developing clear annotation and evaluation instructions. • Reviewed and ranked generative text outputs for linguistic quality and style. • Developed improved guidelines and examples to increase annotation consistency. • Led regular audits of labeled data for compliance and accuracy. • Enhanced evaluation processes for long-form content labeling.

As an NLP / ML Engineer at Grammarly, I conducted evaluations of AI-generated rewrites, focusing on clarity, correctness, and appropriateness for diverse audiences. I carried out detailed audits, fact-checking, and guideline-driven quality assurance of long-form and short-form AI outputs. I improved rater agreement by developing clear annotation and evaluation instructions. • Reviewed and ranked generative text outputs for linguistic quality and style. • Developed improved guidelines and examples to increase annotation consistency. • Led regular audits of labeled data for compliance and accuracy. • Enhanced evaluation processes for long-form content labeling.

2020 - 2022

Research Assistant (NLP)

Text

During my time as a Research Assistant at Allen Institute for AI, I evaluated and analyzed outputs from generative commonsense reasoning models. I designed adversarial prompts for model testing and identified recurring failure modes to inform dataset refinement. I focused on improving factual accuracy and logical coherence through systematic annotation and evaluation. • Created challenging input prompts to probe weaknesses in reasoning models. • Identified errors and documented them for correction and further study. • Analyzed model outputs for logical consistency and factual adherence. • Provided structured feedback for enhancing annotation guidelines.

During my time as a Research Assistant at Allen Institute for AI, I evaluated and analyzed outputs from generative commonsense reasoning models. I designed adversarial prompts for model testing and identified recurring failure modes to inform dataset refinement. I focused on improving factual accuracy and logical coherence through systematic annotation and evaluation. • Created challenging input prompts to probe weaknesses in reasoning models. • Identified errors and documented them for correction and further study. • Analyzed model outputs for logical consistency and factual adherence. • Provided structured feedback for enhancing annotation guidelines.

2019 - 2021

Computational Linguist / Data Annotator

LionbridgeTextClassification

At Lionbridge AI (TELUS International) & Appen, I performed large-scale annotation, grading, classification, and relevance labeling on diverse text datasets. My work involved strict adherence to quality standards, fact-checking protocols, and reviewer feedback loops to ensure high labeling accuracy. I actively contributed to refining annotation guidelines and enhancing data reliability during high-volume remote tasks. • Labeled, classified, and graded text data for multiple commercial and research projects. • Implemented reviewer feedback to raise annotation quality and consistency. • Conducted factual verification as part of annotation task workflow. • Delivered projects independently while meeting stringent deadlines.

At Lionbridge AI (TELUS International) & Appen, I performed large-scale annotation, grading, classification, and relevance labeling on diverse text datasets. My work involved strict adherence to quality standards, fact-checking protocols, and reviewer feedback loops to ensure high labeling accuracy. I actively contributed to refining annotation guidelines and enhancing data reliability during high-volume remote tasks. • Labeled, classified, and graded text data for multiple commercial and research projects. • Implemented reviewer feedback to raise annotation quality and consistency. • Conducted factual verification as part of annotation task workflow. • Delivered projects independently while meeting stringent deadlines.

2017 - 2019

Education

Work History