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Animesh Srivastava

Vice President Gen AI & ML - JPMorganChase | Building AI Agents in production at scale

Bengaluru

9+ years of work experience

JPMorganChase
Nov 20241 yr 11 mosPresent

Bengaluru, Karnataka, India

- Building Advanced Predictive Analytics and GenAI applications for JP Morgan’s suite of products at scale, serving millions of customers around the globe - Managing a team of data scientists and machine learning engineers for advancing GenAI within the firm with focus on building scalable AI Agents
ResMed
May 20231 yr 7 mosNov 2024

Bengaluru, Karnataka, India

- IHS 2.5 (Intelligent Health Signals)- Developed a scalable, production-grade self-serve platform for machine learning applications using AWS, including the full MLOps lifecycle: experimentation, feature engineering, FEAST feature store, model training, CI/CD deployment, and monitoring - Built and deployed an explainable Deep Learning Neural Network for predicting dementia from MRI scans, utilizing LIME projections and SLIC super-segmentation for enhanced interpretability. -Automated infrastructure provisioning with Terraform for batch and real-time inference - Created a data drift, model performance monitoring as well as operational monitoring service using Docker and ECS, continuously scanning incoming data for drifts and triggering model retraining via SQS events without human intervention. Used DataDog for the purpose of monitoring and alerting - Developed and deployed a state of the art drift monitoring solution using Evidently. Provides capability to detect drift in tabular, texts, images as well as LLMs
Yara International
Dec 20211 yr 6 mosMay 2023

Bengaluru, Karnataka, India

- Leading the design, architecture and execution of farm and field data products (FFDP) - Worked with a team of Data Engineers, Data Scientists and Software Developers to build state of the art Data products for Yara - Built a Data Ingestion pipeline for transferring on-premise Database to AWS Redshift, using Python, AWS EKS and Airflow. - Built a production ready platform for MLOps: ML model tracking, versioning, CI/CD for ML deployment on AWS premises as Docker Containers on AWS Fargate - Worked on a Deep Learning project for removing clouds from satellite images using Time Series Forecasting of pixels via Pytorch - Working on Event Driven Architecture using Confluent Kafka, producers, consumers and brokers, KSQL, SinkConnectors consuming data from Kafka bus Tech Stack: Machine Learning, MLOps using Mlflow, Cloud Engineering, ETL pipelines, Airflow, Deep Learning , Tensorflow, MLDeployment, Docker, Kubernetes, AWS Fargate, AWS ECS, Load Balancer, API gateway, Apache Kafka, AWS Lake Formation, AWS Glue
o9 Solutions, Inc.
Mar 20201 yr 10 mosDec 2021

Bangalore Urban

- Building forecasting pipelines for Demand Planning and Inventory Management - Created curated algorithms for identification of similar products for an NPI - Scaling ML models that allow continuous training and continuous deployment
IQVIA
Jul 20162 yrs 8 mosFeb 2019

Bangalore, India

-Develop models to predict the patient population for clinical trials in UK -Automation of critical business processes using Python, Pyspark -Using Machine Learning to predict the patient journey

Animesh’s AI Stack

langchain
langchain
langfuse
langfuse
langgraph
langgraph
langsmith
langsmith
claudecode
claudecode
huggingface
huggingface

Education

Birla Institute of Technology, Mesra

Bachelor in Engineering, Electronics and Communication Engineering

Birla Institute of Technology, Mesra

20124 yrs2016
Asian Institute of Management

Master of Science - MS, Data Science

Asian Institute of Management

20191 yr2020

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Headline

Vice President Gen AI & ML - JPMorganChase | Building AI Agents in production at scale

About

Full Stack Machine Learning Scientist with deep expertise in core Machine Learning, Deep Learning and LLMs. Have worked on multiple use cases spanning healthcare and finance domains. In addition to the core data science modelling, have worked extensively on the ML engineering and MLops on top of AWS, Kubernetes and Sagemaker to deploy and scale AI applications, catering to thousands of end-users around the globe. Currently, working specifically on AI agents to solve complex use cases. A hands-on technical leader specialised in architecting and building AI products from scratch as well as defining the strategy for AI/GenAI, stakeholder management and scaling teams. 🔹Machine Learning 🔹Deep Learning 🔹LLMs 🔹AWS🔹Kubernetes 🔹MLops 🔹AI Agents 🔹Data Platforms 🔹SDLC🔹Thought Leadership

Location

Bengaluru

AI stack

langchain

langfuse

langgraph

langsmith

claudecode

huggingface

Work experience

Vice President - GenAI and Applied ML at JPMorganChase, Nov 2024 - Present · 1 yr 11 mos, Bengaluru, Karnataka, India, - Building Advanced Predictive Analytics and GenAI applications for JP Morgan’s suite of products at scale, serving millions of customers around the globe - Managing a team of data scientists and machine learning engineers for advancing GenAI within the firm with focus on building scalable AI Agents

Staff Machine Learning Engineer at ResMed, May 2023 - Nov 2024 · 1 yr 7 mos, Bengaluru, Karnataka, India, - IHS 2.5 (Intelligent Health Signals)- Developed a scalable, production-grade self-serve platform for machine learning applications using AWS, including the full MLOps lifecycle: experimentation, feature engineering, FEAST feature store, model training, CI/CD deployment, and monitoring - Built and deployed an explainable Deep Learning Neural Network for predicting dementia from MRI scans, utilizing LIME projections and SLIC super-segmentation for enhanced interpretability. -Automated infrastructure provisioning with Terraform for batch and real-time inference - Created a data drift, model performance monitoring as well as operational monitoring service using Docker and ECS, continuously scanning incoming data for drifts and triggering model retraining via SQS events without human intervention. Used DataDog for the purpose of monitoring and alerting - Developed and deployed a state of the art drift monitoring solution using Evidently. Provides capability to detect drift in tabular, texts, images as well as LLMs

Data Platform Architect at Yara International, Dec 2021 - May 2023 · 1 yr 6 mos, Bengaluru, Karnataka, India, - Leading the design, architecture and execution of farm and field data products (FFDP) - Worked with a team of Data Engineers, Data Scientists and Software Developers to build state of the art Data products for Yara - Built a Data Ingestion pipeline for transferring on-premise Database to AWS Redshift, using Python, AWS EKS and Airflow. - Built a production ready platform for MLOps: ML model tracking, versioning, CI/CD for ML deployment on AWS premises as Docker Containers on AWS Fargate - Worked on a Deep Learning project for removing clouds from satellite images using Time Series Forecasting of pixels via Pytorch - Working on Event Driven Architecture using Confluent Kafka, producers, consumers and brokers, KSQL, SinkConnectors consuming data from Kafka bus Tech Stack: Machine Learning, MLOps using Mlflow, Cloud Engineering, ETL pipelines, Airflow, Deep Learning , Tensorflow, MLDeployment, Docker, Kubernetes, AWS Fargate, AWS ECS, Load Balancer, API gateway, Apache Kafka, AWS Lake Formation, AWS Glue

Senior Data Scientist at o9 Solutions, Inc., Mar 2020 - Dec 2021 · 1 yr 10 mos, Bangalore Urban, - Building forecasting pipelines for Demand Planning and Inventory Management - Created curated algorithms for identification of similar products for an NPI - Scaling ML models that allow continuous training and continuous deployment

Data Scientist at IQVIA, Jul 2016 - Feb 2019 · 2 yrs 8 mos, Bangalore, India, -Develop models to predict the patient population for clinical trials in UK -Automation of critical business processes using Python, Pyspark -Using Machine Learning to predict the patient journey

Education

Bachelor in Engineering, Electronics and Communication Engineering, Birla Institute of Technology, Mesra

Master of Science - MS, Data Science, Asian Institute of Management