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About Manikanth Reddy

Hello there,

Thanks for taking time to know more about me. My name is Manikanth Reddy (you can call me Mani). You can contact me through the information provided in this page.

Disclaimer:

This is my personal website and the views expressed here are mine alone and do not necessarily reflect the views of my employer, unless and until I mention it in the corresponding page. Please go through the full disclaimer here.

Summary

Currently, I work as a Staff Machine Learning Engineer at Bloomreach, where I develop and deploy machine-learning and AI systems for large-scale e-commerce applications. My work focuses on search, personalization, recommendation systems, and applied generative AI. I also provide technical leadership on ML projects and mentor other engineers. While working as a Senior Machine Learning Engineer, I served as the ML Tech Lead for the Recommendations product line.

Before I joined Bloomreach, I worked as an Data Scientist (Machine Learning) at American Express. I was a part of Machine Learning and Data Science (MLDS) Research team based out of Bangalore, India. As part of the team, I worked on solving a broad range of problems related to Credit and Fraud Risk.

In my free time, I work on Kaggle, go on trips (Bike trips are ❤️) or read manga (can talk days about One Piece, Haikyuu and Jujustu Kaisen, if you are into it). I also play Tennis, Table Tennis, Cricket, Badminton and Volley Ball.

Interests

My current ML research interests include:

  • Search & Recommendation systems

  • Multi-modal representation learning

  • Natural language processing and language models

  • Self-supervised and semi-supervised Learning

Bloomreach

I joined Bloomreach in 2021 and currently work as a Staff Machine Learning Engineer.

Current work

My current responsibilities include:

  • Designing, developing, and optimizing ML/AI models for search relevance, personalization, and recommendation systems.

  • Researching and productionizing deep-learning techniques including transformer-based models, embedding methods, and model-training optimization.

  • Building ML systems supporting conversational and generative-AI applications.

  • Developing and maintaining production machine-learning training and serving pipelines.

  • Designing A/B testing and model-evaluation methodologies for ML-driven features.

  • Working with engineers, product managers, and data scientists to deploy ML systems at scale.

  • Contributing to ML-system architecture, retrieval, ranking, and automated ML-development workflows.

  • Mentoring machine-learning engineers and providing technical guidance on model development, experimentation, and production deployment.

Earlier work at Bloomreach

Earlier in my time at Bloomreach, I worked extensively on recommendation systems, visual search, multilingual attribute extraction, similar-product recommendations, and personalization. As a Senior Machine Learning Engineer, I also served as the ML Tech Lead for the Recommendations product line.

American Express

Before joining Bloomreach, I worked as an Analyst in the Machine Learning and Data Science (MLDS) Research Team at American Express (India) in Bangalore from July 2019 to May 2021.

My work focused on applying machine learning and deep learning techniques to problems involving financial transaction data, credit risk, fraud risk, and natural language processing.

One of my primary projects involved bank statement transaction classification using Natural Language Processing and deep learning.

  • I designed and developed neural-network classification models for categorizing bank statement transactions.

  • I worked with text representation techniques including Word2Vec, FastText, tokenization strategies, and other natural-language-processing approaches.

  • I helped improve the response time of the production ML system through code optimization and caching techniques, allowing the system to better meet its latency and SLA requirements.

  • I contributed to building a production inference API and deploying machine-learning models using Docker-based infrastructure.

  • I worked on extending machine-learning models across different markets and improving their ability to generalize across different datasets and languages.

As part of the Machine Learning and Data Science Research Team, I also worked on several other machine-learning and research initiatives, including:

  • Improving Recurrent Neural Network (RNN) models used for credit and fraud-risk applications.

  • Exploring Graph Neural Networks for modeling relationships in financial data.

  • Developing approaches for optimizing multiple business objectives simultaneously, including competing model-performance metrics.

  • Exploring model-compression techniques such as Knowledge Distillation.

  • Researching adversarial attacks and robustness of machine-learning models used for fraud detection.

  • Experimenting with attention-based neural networks and other deep-learning architectures.

  • Working on forecasting problems using machine-learning models such as XGBoost.

The role gave me practical experience across the machine-learning lifecycle, including model research, experimentation, software engineering, production deployment, optimization, and collaboration with large cross-functional teams.

I also presented several technical learning sessions to colleagues within the Bangalore Decision Science organization, including:

  • PyTorch — From Basics to Advanced

  • Machine Learning Research Topics

  • Knowledge Distillation

During my time at American Express, I received the SVP Star Achievement Award for Q4 2019 as part of the Decision Science & Data Strategy organization.

IIT Kharagpur

I received my Bachelor of Technology (Honours) in Metallurgical and Materials Engineering from the Indian Institute of Technology, Kharagpur in 2019.

Although my primary degree was in Metallurgical and Materials Engineering, I developed a strong interest in programming, machine learning, and data science during my undergraduate studies through coursework, independent learning, competitions, internships, and personal projects.

Some of the relevant coursework I completed included:

  • Programming and Data Structures

  • Programming and Data Structures Laboratory

  • Design and Analysis of Algorithms

  • Artificial Intelligence

  • Soft Computing Tools

  • Probability and Stochastic Processes

  • Computer Applications in Metallurgical Processes

  • Engineering Drawing and Computer Graphics

I also supplemented my university coursework with online courses and independent study in areas such as:

  • Machine Learning

  • Applied Data Science with Python

  • Deep Learning

  • TensorFlow

  • Natural Language Processing

  • Neural Networks

During my time at IIT Kharagpur, I participated in several technical competitions and hackathons:

  • HSBC Data Science Hackathon — Our five-member team finished in second place, and we were invited to the HSBC Data & Analytics Symposium 2019 in Kolkata.

  • American Express Analyze This 2018 — Our two-member team finished among the top teams in the competition. I subsequently received a Pre-Placement Interview opportunity from American Express, which eventually led to my joining the Machine Learning and Data Science team after graduation.

  • Microsoft Code.Fun.Do 2015 — As part of a three-member team, I helped build an application in C# during the competition.

I also completed a Data Science internship at Innoplexus Consulting Services in 2018, where I worked on entity extraction, word-sense disambiguation, entity extraction APIs, and data-processing pipelines.

Outside academics, I served as the Web Development Lead for COMPOSIT, the annual technical festival organized by the Department of Metallurgical and Materials Engineering at IIT Kharagpur. I led a team of five students responsible for developing the website for the 25th edition of the event.

I am also a Dakshana alumnus. During college, I volunteered in organizing the Grand Dakshana Selection Test for multiple years and served as a college representative for the organization.

Jawahar Navodaya Vidyalaya

I completed by 12th Standard from Jawahar Navodaya Vidyalaya, Gachibowli as a Dakshana Scholar. I become a Dakshana Scholar after clearing the Grand Daskhana Selection Test 2013. Dakshana is an NGO registered in India.