Sahil Dhakate

Backend Engineer

Nagpur, Maharashtra, India0 mo experience
AI EnabledAI ML Practitioner

Key Highlights

  • Improved LLM-driven chat accuracy by 35%.
  • Designed emotion detection system with 85% accuracy.
  • Established robust code quality practices reducing violations by 85%.
Stackforce AI infers this person is a Backend Developer specializing in AI and Blockchain solutions for Healthcare and Software Development.

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Skills

Core Skills

Backend DevelopmentAi InfrastructureNlp

Other Skills

Advanced JavaAdvanced MathematicsAlgorithm AnalysisAlgorithmsBack-End Web DevelopmentBlockchainC (Programming Language)C#C++Cascading Style Sheets (CSS)Code ReviewCore JavaData ScienceData StructuresDatabases

Experience

0 mo
Total Experience
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Average Tenure
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Current Experience

Advocara

BackEnd Developer

Nov 2024Present · 1 yr 7 mos · Reston, Virginia, United States · Remote

  • Drove core enhancements to AI infrastructure and data pipelines that directly improved LLM-driven chat summarization accuracy by 35% and reduced medical information loss by 25%, aligning closely with product reliability goals in healthcare use cases. Delivered high-precision chat restoration capabilities with high recovery rate, lowering support volume by 20% and improving user trust.
  • Co-developed a dynamic prompt enhancement engine that enriched LLM input with curated insights from unstructured sources, increasing response precision by 30% and improving knowledge coverage. Architected a configurable retry framework with exponential backoff and intelligent error handling, boosting system resilience and reducing transient API failures by 40%.
  • Established robust code quality practices by integrating the Ruff linter at scale, leading to an 85% drop in lint violations and earlier defect detection. These initiatives improved both platform stability and engineering velocity across the team.
JavaPythonLarge Language Models (LLM)Systems DesignMachine LearningBlockchain+2

R3 systems india private limited

Software Intern

Dec 2021Jan 2022 · 1 mo · Nashik, Maharashtra, India · Hybrid

  • Designed and deployed an automated emotion detection system leveraging advanced NLP techniques, achieving 85% classification accuracy across multi-sentence inputs.
  • Applied machine learning algorithms to refine sentiment prediction models, driving a 20% improvement in accuracy and enabling more nuanced emotion analysis.
  • Implemented scalable sentiment analysis pipelines using diverse NLP methods, resulting in a 90% accuracy rate and significantly enhancing the overall precision of sentiment detection systems.
Natural Language Processing (NLP)Machine LearningSentiment AnalysisNLP

Education

Dr. Babasaheb Ambedkar Technological University (DBATU)

Bachelor of Technology - BTech — Computer Engineering

Aug 2019Jun 2023

Centre for Development of Advanced Computing (C-DAC)

PG-DAC — Computer Engineering

Sep 2023Feb 2024

Indian Institute of Technology, Kanpur

Professional Certification Program in Blockchain — Blockchain Technology

Apr 2023Jul 2023

Indian Institute of Technology Hyderabad

Professional Certification Program in Artificial Intelligence and Emerging Technology — Machine Learning

Jun 2021Dec 2021

Adarsh Sanskar Vidyalaya and Junior College, Nagpur

12th — Non-Medical

Jun 2017Apr 2019

Mahila Samaj High School Bhandara

10th

Jan 2017Present

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