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Khushal Tiwari

@khushaltiwari

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AI and data professional specializing in LLM training, data pipelines, and fraud investigation.

India

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What I'm looking for

I seek roles where I can apply LLM training and data pipeline skills, collaborate cross-functionally, and drive measurable model and risk-reduction impact.

I am an AI and data professional with hands-on experience in LLM training, data preparation, and large-scale risk investigation at Amazon. I have contributed to labeling, ranking, and evaluating model outputs, automated data pipelines using Python and SQL, and collaborated with ML engineers and stakeholders to improve model performance and data quality.

My background includes detecting and mitigating ecommerce fraud, conducting SQL-driven transaction analysis, and producing actionable investigation reports. I emphasize rigorous data preprocessing, reproducible documentation, and cross-functional problem solving to deliver reliable, high-quality outcomes in dynamic environments.

Experience

Work history, roles, and key accomplishments

Current

Freelance LLM Trainer/Engineer

Current

Mercor

Mar 2025 - Present (11 months)

I created, refined, and structured high-quality multi-turn conversations between users and AI assistants to train models.
Designed scenarios that simulated real-world reasoning, guiding assistants to use tools to complete tasks.
Worked with RLHF (Reinforcement Learning from Human Feedback) techniques to align models with user preferences, tone, and safety guidelines.

Python LLM Data Analysis Data Pipelines

Investigation Specialist

Amazon

Sep 2022 - Mar 2024 (1 year 6 months)

Investigated and eliminated e-commerce risks including payment fraud, account takeovers, and fake reviews, reducing operational loss and improving platform trust; collaborated with legal, product, and operations to resolve complex cases and optimize processes.

Fraud Investigation SQL Excel BI Tools Risk Mitigation Data Analysis Reporting Cross Functional Collaboration

Machine Learning Data Associate

Amazon Development Centre

May 2021 - Jul 2022 (1 year 2 months)

Contributed to LLM training and data preparation by labeling, ranking, and evaluating model outputs, automating data pipelines with Python and SQL to improve dataset quality and model performance.

Data Labeling Python SQL data preprocessing & QA