Hardik Kalra

AI Researcher

United States2 yrs 2 mos experience

AI EnabledAI ML Practitioner

Key Highlights

Expert in fine-tuning AI models for enhanced accuracy.
Proven track record in data-driven insights and automation.
Strong background in prompt engineering for AI applications.

Stackforce AI infers this person is a Data Science and AI specialist with a focus on healthcare and education sectors.

Contact

hkalra_be19@thapar.edu LinkedIn

Skills

Core Skills

Data ScienceArtificial Intelligence (ai)

Other Skills

AI modelsAPIsAlgebraAlgorithmsAmazon Web Services (AWS)Analytical SkillsAnalyticsAttention to DetailAutomated ReasoningBrandingBusiness AnalysisBusiness DevelopmentBusiness InsightsC (Programming Language)C++

Experience

Turing

Research Analyst

Jan 2025 – Present · 1 yr 2 mos · United States · Remote

Fine-tuned LLM models using Supervised Fine-Tuning (SFT) on JEE and Olympiad-level mathematics problems, optimizing accuracy and structured reasoning.
Designed and implemented advanced prompting techniques with deep mathematical research, leveraging AI models like O-1 Preview and GPT-4o to ensure clarity and correctness in solutions.
Led AI data training and annotation processes, utilizing labeling tools to create high-quality datasets for enhanced model learning and performance.
Reviewed and refined data labeling done by junior engineers and new joiners, ensuring precision, consistency, and adherence to project standards.
Optimized LLMs using RLHF and data science techniques, improving model precision, dependability, and real-world problem-solving capabilities across diverse industries.

Fine-tuning LLM modelsData training and annotationSupervised Fine-Tuning (SFT)AI modelsData labelingData Science+1

Soul ai

Prompt Engineer

Jun 2024 – Jul 2024 · 1 mo · United States · Remote

Developed and fine-tuned interactive prompts for large language models (LLMs), improving response accuracy and relevance by 25%, leading to enhanced AI-driven interactions.
Collaborated with subject matter experts (SMEs) to integrate industry-specific terminology, boosting prompt effectiveness and user engagement by 15%.
Conducted data annotation and labeling for text-based NLP tasks and image datasets, ensuring high-quality training data for AI models.
Monitored prompt performance in real-world scenarios, analyzed feedback, and iteratively optimized AI-generated responses, streamlining the data collection and decision-making process.

Interactive promptsData annotationNLP tasksPerformance monitoringArtificial Intelligence (AI)Data Science

Medlr

Data Scientist

Jan 2024 – Jan 2025 · 1 yr · Chandigarh, India · Remote

Developed the RapidFuzz technology algorithm using NLP, reducing medication errors by 30% and processing data from 697,620 medicines across top pharmacies for precision and efficiency.
Automated web scraping for pharmaceutical data from platforms like Tata1mg, Pharmeasy, and Netmeds, integrating it into ElasticSearch to enhance data-driven insights.
Designed a scheduling system for periodic data updates, expanding the dataset by 30% year-on-year while tracking price changes.
Leveraged multithreading to accelerate data extraction and improve throughput, driving greater efficiency and productivity.

NLPWeb scrapingElasticSearchData automationData processingData Science+1

Travel friend

AI Research and Development

Jul 2023 – Dec 2023 · 5 mos · New Delhi, Delhi, India · On-site

Implemented advanced APIs including Gemini, OpenAI, and Hugging Face into Langchain initiatives, resulting in a 30% boost in AI performance and reducing development time by 35%, leading to faster project completions.
Built Streamlit NER app and QA app using Langchain tech.
Annotated CUAD datasets and FINE‑TUNED SpaCy and LLM models.
Mastered prompt engineering techniques to optimise large language model outputs, resulting in a 40% increase in response accuracy and a 25% reduction in processing time.

APIsLangchainStreamlitPrompt engineeringData annotationArtificial Intelligence (AI)+1

Outlier

Prompt Engineer

May 2023 – Present · 2 yrs 10 mos · United States · Remote

Designed, tested, and refined prompts for AI models in Kepler-RLHF, Psychic - Kadabra, Cypher-RLHF, and Bee-SFT-Multilingual projects, ensuring accuracy in physics and mathematics problem-solving.
Developed optimized prompt structures to enhance AI-generated responses, improving reasoning, clarity, and contextual understanding.
Evaluated AI models for regional English (IN), refining linguistic accuracy and contextual appropriateness for diverse user interactions.
Conducted systematic AI performance analysis, leveraging RLHF and SFT techniques to improve model reliability and response quality.
Collaborated with multidisciplinary teams to enhance prompt-based AI training workflows, contributing to advancements in AI-driven problem-solving.

Prompt engineeringAI modelsPhysics and mathematics problem-solvingRLHFSFT techniquesArtificial Intelligence (AI)+1