Ritesh Patil

AI Researcher

Bengaluru, Karnataka, India5 yrs 7 mos experience

Most Likely To SwitchAI ML Practitioner

Key Highlights

Expert in Generative AI and MLOps.
Proven track record in deploying complex ML systems.
Strong background in computer vision and deep learning.

Stackforce AI infers this person is a Machine Learning Engineer specializing in AI solutions for healthcare and computer vision applications.

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Skills

Core Skills

Generative AiMlopsComputer VisionData AnalysisMachine Learning

Other Skills

Retrieval-Augmented Generation (RAG)DockerInformation RetrievalAmazon Web Services (AWS)AWSFastAPIYOLOv5BLIP modelOpenAI whispergpt-3.5-turbo APIPython (Programming Language)C++Deep LearningImage ProcessingExplainable Artificial Intelligence

About

Machine Learning Engineer with 4+ years of experience working on MLops, computer vision, deep learning, LLMOps and Gen AI

Experience

5 yrs 7 mos

Total Experience

1 yr 1 mo

Average Tenure

1 yr 7 mos

Current Experience

Accenture

Senior Data Scientist

Oct 2024 – Present · 1 yr 7 mos · Bengaluru · Hybrid

Built and deployed multiple Retrieval-Augmented Generation (RAG) systems using Azure OpenAI, integrated with both AWS RDS (Postgres) and AWS OpenSearch as vector stores.
Implemented hybrid retrieval (keyword + semantic search) and applied cross-encoder reranking to ensure high contextual relevance of results.
Orchestrated deployments using FastAPI, AWS ECS, AWS ECR, AWS Lambda, and AWS API Gateway.
Developed and automated data processing pipelines using AWS Glue for scalable ingestion and transformation.

Generative AIRetrieval-Augmented Generation (RAG)DockerInformation RetrievalAmazon Web Services (AWS)MLOps

Valere

Software Engineer-Machine Learning

Mar 2024 – Oct 2024 · 7 mos · Pune, Maharashtra, India · On-site

Scene Description of Video using YOLOv5, BLIP model, OpenAI whisper and gpt-3.5-turbo API.
Fine Tuning of Vision Transformer model for identification of Famous Celebrities.
Developed a robust RAG framework using OpenAI embeddings and Pinecone as vector database, along with guardrails.

Yantravision software

Computer Vision Engineer

Dec 2023 – Feb 2024 · 2 mos · Bengaluru, Karnataka, India · On-site

Detection of individual flap area and panel area present on the carton using image processing techniques.
Mapped coordinates of detected flaps and panels across different cameras based on affine transformations and non linear camera positioning.
Detection of Braille region present on the carton using deep learning.
Identifying defects in the Braille region using image processing.

Python (Programming Language)C++Deep LearningComputer Vision

Insight sfi centre for data analytics

Research Scientist

Sep 2022 – Oct 2023 · 1 yr 1 mo · Dublin City, County Dublin, Ireland

Designed and developed End-to-End Data Pipelines for Automatic Reading of Analogue Weighing Scale using Python, Deep Learning, Optical Character Recognition (OCR) and AWS.
Designed, developed and fine-tuned Convolutional Neural Network (CNN) for the use case of Automatic Reading of Analogue Weighing Scale using tensorflow.
Developed Regulatory Framework for integration of AI into medical devices in terms of MLOps.
Former Consultant to European Commission on behalf of Insight for practical adoption of AI act in medical domain.

Data AnalysisExplainable Artificial IntelligenceDeep LearningMLOps

Magnus monitors ( eirscope limited )

Data Analyst Intern

Dec 2021 – Aug 2022 · 8 mos · Galway, County Galway, Ireland

Worked on AutoML specifically targeted towards Computer Vision using AWS Custom Recognition Label Service.
Developed Python Web Automation Scripts for simplifying routine work.

Data AnalysisAmazon Web Services (AWS)Deep Learning

Accenture in india

Junior Data Scientist

Sep 2019 – Jul 2021 · 1 yr 10 mos · Pune, Maharashtra, India

Developed Image Preprocessing pipelines of Angiograms collected from Angiography devices as part of feature engineering.
Part of team responsible for designing and fine-tuning light weight deep learning models such as EfficientDet with custom data.
Deployed Light weight deep learning models on edge devices using tensorflowlite and docker.
Summarized the project and future-plan to new members in the team by organizing a knowledge
transfer session.

Explainable Artificial IntelligenceDeep LearningMachine Learning

Etlhive

Student/Data Analyst Intern

Dec 2018 – Jun 2019 · 6 mos · Pune

Performed Statistical analysis on real time Financial Data.
Developed number of End-to-End Deep Learning Models with deployment using flask and Docker.
Performed time series analysis and forecasting on real time Medical data.
Learnt and applied basic Machine learning algorithms on small datasets for learning purposes.