Niliza Peoples

Key Skills

Software

Clickworker

Labelbox

Lionbridge

Remotasks

Scale AI

Top Subject Matter

Multiturn deviations for RLHF in LLM

Claim verification

rating/ranking evaluation tasks

Training LLMs on Multiturn deviations using RLHF

Top Data Types

Document

Text

Video

Top Label Types

Classification

Evaluation Rating

RLHF

Text Generation

Text Summarization

Freelancer Overview

I have 2-3 years of experience in data labeling and AI training in which I have worked on various projects: LLM training on Multiturn deviation with RLHF, Claim verification evaluations, ranking/ranking evaluations and QA reviewing, prompt writing reviewing and correcting, image and video annotations, text classification, summarization and generation. My key skills are my experience in AI training as well as my professional experience in data analytics and research. I have used various tools and am a fast learner that tech savvy, I ensure accuracy through attention to detail and developing a working knowledge and competency in instructional material/criteria and guidelines provided for each project. I have also worked with domain-specific labeling guidelines and standards to ensure the quality and consistency of the labeled data. In terms of specific tools and software, I have experience with popular data labeling platforms such as Labelbox, Amazon Mechanical Turk, remotasks, Appen and clickworker. I am proficient in using annotation tools for image and video annotations. For text classification and summarization tasks I have used various tools available through identified platforms. I have worked with various industries and domains in data labeling and AI training data, including healthcare, e-commerce, and social media. This has given me exposure to different types of data and helped me understand the specific requirements and challenges of each domain. My experience work

Labeling Experience

LLM Training- Various techniques and objectives

Scale AITextText GenerationText Summarization

Various projects focused on LLM training using a variety of techniques. Utilized ranking criteria to rate, segmenting, quality assurance reviewing, text generation and summarization evaluations, and text and image annotation to support positive changes in language models.

Various projects focused on LLM training using a variety of techniques. Utilized ranking criteria to rate, segmenting, quality assurance reviewing, text generation and summarization evaluations, and text and image annotation to support positive changes in language models.

2020 - 2023

Education

Work History