Prashant J.

About Me

Prashant is an AI/ML Engineer with 6+ years of experience developing AI-powered solutions using Large Language Models, machine learning, and conversational AI. Proven track record of building scalable systems that increase business metrics by up to 18%. Expert in open source LLMs fine-tuning, RAG implementation, and real-time AI deployment. Successfully led development of interview platforms, resume parsers, and recommendation engines serving millions of users.

AI, ML & LLM

Backend

Python REST APIs

DevOps

Other

Clustering Algorithms Data Science Fine-tuning Hugging Face Keras LoRa NLP Numpy Pandas Prompt Engineering Quantization RAG Stakeholder management Team Leadership Tensorflow WebSockets Word2Vec

Work history

Deloitte
Deloitte
Lead Data Scientist
2023 - Present (2 years)
Gurgaon, India
  • Leading a team of engineers and data scientists to develop an AI-powered interview platform using LLaMA 3.1, fine-tuned with LoRA and QLoRA, reducing client interview scheduling time by 60% and improving candidate experience scores by 85%.

  • Leading the development of an intelligent resume parser using fine-tuned LLaMA2 13B model with parameter-efficient fine-tuning, achieving 91% accuracy in structured data extraction.

  • Developed Job Description to resume matching engine using embeddings and RAG architecture, increasing successful placement rates by 35% and reducing time-to-fill by 45%.

  • Implemented semantic search with Qdrant vector database and multi-query decomposition for enhanced relevance matching.

  • Spearheaded the Auto-Calling Engine project, increasing candidate screening efficiency by 300% and lowering cost-per-hire by 40%.

LLaMA 3.1 LoRa QLora VLLM Deepgram RAG Qdrant embeddings Data ScienceAI/ML Data Extraction Parsers Vector Databases Generative AI Natural Language Processing (NLP) Large Language Models (LLMs) Data pipelinesLangChain TransformersAgentic AI PythonRetrieval-augmented Generation (RAG) MCP
PharmEasy
PharmEasy
Senior Data Scientist
2021 - 2023 (2 years)
Bangalore, India
  • Developed a comprehensive recommendation engine platform combining collaborative filtering and NLP-based matching systems, resulting in an 18% increase in Click Through Rate and 9% increase in Add To Cart metrics across the platform through rigorous A/B testing.

  • Developed an intelligent medicine name normalization system using Siamese Network for automated product matching with PharmEasy golden master database, increasing automapping percentage by 12% and reducing the Data Governance team's manual workload by 200+ hours weekly.

  • Implemented an NLP solution that handles product name variations, spelling errors, and brand synonyms, enabling seamless product catalog management and improving inventory accuracy by 25%.

  • Trained Word2Vec on the transaction data to generate most frequently used items with respect to a given item.

Siamese Network Data ScienceNatural Language Processing (NLP) A/B TestingAWSSocket Programming Collaborative Filtering SQLTransformersMongoDBRecommendation Systems Word2Vec
Accenture
Accenture
Data Scientist
2019 - 2022 (3 years)
Gurgaon, India
  • Built a comprehensive talent intelligence platform using Named Entity Recognition and knowledge graph algorithms to extract skills from resumes, create skill ontologies with Word2Vec embeddings, and develop reskilling frameworks using Trans-E algorithms, reducing bench size by 30% and improving internal mobility by 45%.

  • Developed a predictive analytics suite for workforce optimization including time series forecasting models for demand-supply-attrition gaps and employee exit analysis using clustering algorithms to identify retention drivers, enabling proactive talent planning and reducing attrition costs by 20% across service lines.

  • Developed a Deep Learning-based model (NER) to extract skills and job title from resumes and job descriptions.

  • Developed a keyword summarization module using Selenium (extracted 100 pages of a particular keyword), TFIDF (extracting important words), language model (generating embeddings from keywords-pretrained model), clustering using generated embeddings.

  • Worked on dashboard development using d3.js and JavaScript.

Named Entity Recognition Trans-E TransformersKnowledge Graphs Predictive AnalyticsData ScienceTime Series AnalysisWord2Vec Clustering Algorithms Machine LearningKerasApache SparkAWSAWS Lambda PythonDashboard Development d3.jsJavaScriptDeep LearningSeleniumWorkforce Management (WFM)
EDGE
EDGE
Data Scientist
2018 - 2019 (1 year)
Bangalore, India
  • Improved user experience through Data Science to deliver compelling value in profile manager.

  • Worked on title normalization to improve the quality of the search & match product.

  • Worked on an NLP-based model to segment different sections from resumes (personal information, projects, skills, certifications).

  • Tagged ~60K resumes and trained classifiers on top of it.

NLPData ScienceDocument Parsing Parsers UX

Education

Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization | Neural Networks and Deep Learning | Structuring Machine Learning Projects
Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization | Neural Networks and Deep Learning | Structuring Machine Learning Projects
Coursera
2017 - 2017
B.Tech ECE
B.Tech ECE
The LNM Institute of Information Technology - India
2014 - 2018 (4 years)