Machine Learning Product Development, Data Engineering, AI

Bhaskar Bhattacharyya

Pursuing Director of AI/ML engineering role where I can leverage my expertise in Data/ML/AI engineering and engineering leadership to contribute to business growth and further my professional development.

Summary

●Expert in Distributed Database development and Data/ML/AI Engineering

●Have extensive experience in developing products/services for large companies like Microsoft, VMware, and smaller tech start-ups

●10+ years of FTE experience at Microsoft Corporation in multiple server product development teams (Microsoft SQL Server, Microsoft BizTalk Server, and Windows Workflow Foundation)

●8+ years as CTO/Data-AI architect at ioCurrents and built data and Machine Learning pipelines, autoML, prescriptive and predictive data analytics platforms, and multiple AI applications

●Experienced in overall software architecture, design, development, implementation, product testing, full cycle agile product development, and shipping of analytics/ML/AI services SAAS products

●Completed Microsoft Azure data fundamental, IBM AI engineering course, and DeepLearning. AI’s Generative AI courses. Hands-on experience in AWS SageMaker

●Have built LLM applications using techniques such as Prompt engineering, Retrieval-Augmented Generation (RAG), Fine Tuning, including PEFT/LoRA

●Awarded the following AI/ML patents, among others:

Data compression and communication using machine learning

Machine Learning-Based Prediction, Planning, And Optimization Of Trip Time, Trip Cost, And/or Pollutant Emission During Navigation

Near Real-Time Detection And Classification Of Machine Anomalies Using Machine Learning And Artificial Intelligence

See the full list of patents awarded to me here.

Skills

• Machine Learning • AI • Generative AI • OpenAI • Azure • AWS/SageMaker • PostgreSQL

• Dynamic SQL • Python • C# • Software Development • Agile Methodologies • Automation

• Distributed Systems • SaaS • PyTorch • Redshift

Experiences

Principal Data Engineer

Ascendion/Amazon contract

April 2025 – till date

Design data pipeline for Amazon sustainability project to compute monthly CMUR (Circular Material Use Rate) numbers. I lead a team of DE and BI engineers and designed/developed the new pipeline to support enhancing CMUR numbers by incorporating component (SSD, HDD, RAM etc) weights that added major economic value for Amazon.

Sr. ML Engineer

UseButton.com

Sep 2024 – Jan 2025

Button acts as a retail sales clickpath actions historian/analytics platform between retailers and publishers and provides sales attribution and clickpath reliability on all OS/environments (Instagram, Facebook etc.) and drives app install. Publisher’s referral links are wrapped in button links and button provides following options.

1.If the retailer app is not already installed - install app and deeplink

2.If retailer app is installed - deeplink (open page)

3.User can choose to open the link in mobile web

4.Optionally display other relevant products ads from Button’s own Advertising platform and partner sales network.

Option 1,2,3 is implemented using a multi-arm bandit model. Option 4 for displaying other relevant Advertisements’ decision comes from a new predictive ML model that we have developed as mentioned below.

Defined ML optimization goal for Button The company was optimizing clickpath journeys before I joined. I explained why optimizing revenue per journey would get button lot more revenue than optimizing clickpath journeys. Essentially, they were using probability instead of mathematical expectations, I changed the decisioning game.

Developed several ML models (SKLearn/LGBM and PyTorch and PyTorch/LGBM hybrid models) to decide when to display other advertisements and when to go for multi-arm bandit model

Developed Amazon SageMaker solution to host the different ML models in an real-time inferencing endpoints. Automated ML training pipelines.

Released the decisioning engine (real-time ML prediction endpoint) on live data with 1000 clicks per second scale.

Data/AI Architect

Contract at Amazon/Wholefoods

Oct 2023 – May 2024

Collaborate with business leaders to define business metrics and translate business definitions to technical architecture/design.

Design/development of BI pipelines, writing distributed queries to analyze petabyte scale timeseries data to extract the required metrics dataset and automated pipeline to present the business metrics information in dashboards for business leaders at Wholefoods marketing

Predict dashboard metrics timeseries trends using AI/ML and detect anomalies

Tools/Technologies: AWS/Amazon Redshift, Glue, Athena, SageMaker, pySpark, Tableau.

Chief Technology Officer

ioCurrents Apr 2015 - Sept 2023

●Designed and developed my own version of timescale DB on postgres with hyper-tables, edge compression and partition management using hosted postgres. Developed data/machine learning pipeline and analytics engine/AI applications for ingesting/storing and analyzing large-scale IIoT sensor data at real-time (streaming data analytics) and implemented AI/ML/Analytics SaaS product stack.

●Developed autoML and ML model management/deployment for ML based anomaly detection using postgres.

●Shipped multiple ML based AI services – ‘predictive analytics’ and ‘voyage optimization’.

●Hired, trained, managed engineering/data science teams and product releases.

Master Developer

Hitachi Vantara

Sep 2014 - Sep 2015

●Developed and owned CI/CD pipeline automation for Hitachi cloud servers business, reported to CEO. Skills: SQL/ Python/ Cloud Computing

Principal Software Engineer/QA Manager

SpaceCurve

Oct 2012 - Jun 2014

●Designed and developed a parallel database for big data/IOT from ground-up with a much higher data ingest rate that analyzes petabyte scale multidimensional data at or near real-time.

●Responsible for scalability & performance testing of the distributed databases and overall QA/release management of SpaceCurve's massively parallel big data/IoT DBMS. Skills: SQL/ Python / Cloud Computing

Senior Member of Technical Staff

VMware

Oct 2011 - Oct 2012

●Developed cloud server test strategy & automation of petabyte scale Mozy.com cloud.

●Lead cloud server application testing for VMWare's VMDR project (Disaster Recovery).

●Owned functionality, performance, scalability, reliability & stress testing. Skills: Python / C++/ Cloud Computing

Sr. SDE/T

Research In Motion RIM

Oct 2010 - Oct 2011

●Lead tester of native apps on Playbook (email/calendar/contacts/Facebook).

●Developed test strategy/ architecture for RIM Playbook & BB10 native apps testing (on QNX OS). Provided test automation solution for RIM's new QNX platform.

●Skills: Java/ C++/ Cloud Computing

Software Design Engineer

Microsoft

Nov 2001 - Oct 2010

●Worked as SDE and SDE/T in BizTalk Server, Windows Workflow Foundation, PerformancePoint and SQL Server core product teams, primarily focused on server performance, stress testing, bug fixes, scalable designs & fuzz testing.

●Developed internal fuzz testing tool called XGen that generates arbitrarily complex pseudo random non-terminals from input grammar/ABNF. Skills: Microsoft SQL Server, C#, C++

Senior Software Engineer

Aditi Technologies

Jan 1999 - Jan 2001

●Worked as consultant at Microsoft MSN team. Built help files compiler for word-wheel functionality that searches a compiler generated B-tree file to find matching words.

●Skills: Microsoft SQL Server, C++

Education

IIEST, Shibpur

BE, Electrical Engineering

Portland State University - School of Business

MBA

Honors & Awards

Patents:https://patents.justia.com/inventor/bhaskar-bhattacharyya

Courses

●Microsoft Azure Cosmos DB

●https://coursera.org/share/05ae035f537701ef8920e67dd649ed94

●Core Data Concepts in Microsoft Azure

●https://coursera.org/share/874e3469e55359d28122b88233b27eec

●Microsoft Azure SQL

●https://coursera.org/share/f1c0e6122946869252cb353ea6b2d42d

●Data Warehouse Analytics in Microsoft Azure

●https://coursera.org/share/88eb42d6373040168c0d462a17527abc

●IBM AI Engineering Professional Certificate

●https://coursera.org/share/85401ad80ffefcacad5d5a09eaaa32dc

●DeepLearning.AI - Generative AI with Large Language Models https://coursera.org/share/fb5dd190e4155485b67c8ca5875b4dd2

●Practical Deep Learning for Coders – Fast.AI

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