Highly skilled AI Engineer with 4+ years of experience in developing scalable AI and machine learning solutions using Python, Generative AI, and cloud platforms (Azure, AWS). Proven expertise in RAG systems, LLM fine-tuning, and end-to-end AI platform development, with a strong track record of delivering high-impact enterprise AI applications and leading technical initiatives.
Senior Member of Technical Staff
Pune, Maharashtra, India
→
Summary
Led end-to-end AI/ML solution development and client engagement, driving architectural decisions and feature implementation for enterprise AI applications.
Highlights
Spearheaded client interactions and project leadership for multiple AI/ML projects, ensuring successful delivery and stakeholder alignment.
Designed and implemented robust system architectures and core logic for scalable AI/ML solutions, including GenAI and RAG systems.
Mentored junior engineers and interns in AI, ML, Python, and cloud technologies, fostering team growth and technical capability.
Automated cloud infrastructure deployment using Terraform scripts for Azure/AWS, streamlining delivery pipelines and improving efficiency.
Recognized as a "Unicorn Team of Quarter 2 of 2023-2024" and "Champion of the month September 2024" for outstanding contributions.
Member of Technical Staff
Pune, Maharashtra, India
→
Summary
Developed and optimized machine learning models for client projects, ensuring high accuracy and efficient deployment while adhering to best coding practices.
Highlights
Optimized the speed of deployed machine learning models by 90% through strategic enhancements, significantly boosting performance.
Successfully delivered multiple client Proof-of-Concepts (POCs) within tight weekly deadlines, demonstrating rapid development and impact.
Developed and trained Supervised and Unsupervised ML algorithms to achieve desired client accuracies and domain expertise.
Conducted extensive Exploratory Data Analysis (EDA) to ensure dataset balance and quality, utilizing various tools for robust data preparation.
Engineered clean, maintainable, scalable, and performance-efficient code, adhering to best practices for modularity and reusability.
→
M.Sc.
Statistics
→
P. G. Diploma
Applied Statistics
→
B.Sc.
Statistics
Awarded By
CCTECH PVT LTD
Honored for outstanding individual performance and significant impact within the organization during September.
Awarded By
CCTECH PVT LTD
Recognized as a top-performing team for exceptional contributions and collaborative achievements within the quarter.
RAG Systems, LLM Fine-tuning, Generative AI (Gen AI), Agentic AI, Machine Learning (Classification, Regression), Deep Learning, Computer Vision, Natural Language Processing (NLP), Anomaly Detection, Hypothesis Testing, Time Series Analysis.
Azure, AWS, Docker, Kubernetes, Terraform, Azure DevOps, Cloud Deployment, Infrastructure as Code.
Python, SQL, Rest API, Git Version Control, Statistics, Exploratory Data Analysis (EDA), Data Modeling, PowerBI.
System Design, Solution Architecture, Architectural Decisions, Core Solutioning, Enterprise AI Applications.
Client Handling, Stakeholder Communication, Project Flow Initialization, POC Management, Project Delivery, Mentoring, Team Leadership.
Summary
Developed an AI platform converting engineering design standards and best practices into automated validation rules, integrated with CAD tools like Siemens NX, to enable early detection of design violations and improve overall design quality and efficiency.
Summary
Built an intelligent search platform to help engineers identify alternative or equivalent components by analyzing structured part attributes and compatibility criteria within product lifecycle management systems (Siemens Teamcenter) and vendor websites.
Summary
Designed an AI-driven system to analyze video streams (live or uploaded) for semantic frame-level behavior analysis, identifying key frames, and supporting ad-hoc behavioral and temporal querying.
Summary
Demonstrated the feasibility and efficiency of using local Large Language Models (LLMs) to automate data extraction from multiple reports for root cause analysis, synthesizing insights and generating hypotheses.