Mahesh Jindal — AI Researcher
I am an Applied Scientist specializing in Research Science and Machine Learning, with a focus on building advanced recommender systems and leveraging cutting-edge research in large language models (LLMs). My work centers around ranking algorithms, representation learning, reinforcement learning, and sequential recommenders to deliver highly personalized user experiences at scale. At Amazon Global Media and Entertainment, I drive personalized recommendations through the use of large-scale datasets and state-of-the-art ML techniques, optimizing user engagement and business impact. With a research background from Columbia University, I integrate decision science to ensure models not only deliver accuracy but also support real-time, data-driven business decisions. My expertise extends to LLMs, representation learning, and model interpretability, enabling smarter, more adaptable systems for content understanding and personalization. Let’s connect if you’re looking for an applied scientist passionate about recommender systems, decision science, and innovative machine learning research to drive business growth. My skillset includes: Research Areas: Recommender Systems, Large Language Models, Natural Language Processing, Reinforcement Learning and Graph Neural Networks. Core Skills: Data Modelling, Statistics, Machine Learning, MLOps, Data Visualization, REST, SOAP, Software Development, Distributed Computing, Operating Systems, Cloud Computing Programming Languages: Java, Python, Scala, R, SQL,JSON, XML, LaTeX. Cloud: AWS, GCP Frameworks: Tensorflow, PyTorch, Spark, Kafka, Hadoop, Scalding, Spring, Django, Flask, Scalatra, Pandas, Numpy, Scikit-Learn, Spacy, NLTK, Dask Databases: PostgresSQL, MySQL, DynamoDb, Redshift, MongoDB, H2, Redis Analytical Softwares: Tableau, Dremio, Power BI Connect with me here - https://topmate.io/maheshjindal ---
Stackforce AI infers this person is a Machine Learning expert in the B2C SaaS industry focusing on personalized user experiences.
Location: New York City, New York, United States
Experience: 6 yrs 5 mos
Skills
- Recommender Systems
- Machine Learning
- Data Science
Career Highlights
- Expert in building advanced recommender systems.
- Strong background in large language models and decision science.
- Proven track record in optimizing user engagement through ML.
Work Experience
Amazon
Applied Scientist II (9 mos)
Applied Scientist I (1 yr 4 mos)
Data Scientist (1 yr 4 mos)
Johnson & Johnson
Research Fellow (3 mos)
Audible
Data Science Research Intern (6 mos)
Columbia University in the City of New York
Graduate Teaching Assistant - Large Scale Stream Processing (5 mos)
Graduate Teaching Assistant - Reinforcement Learning (3 mos)
Columbia University Department of Computer Science
Graduate Research Assistant - IRT Lab (11 mos)
FICO
Software Engineering - Engineer 1 (2 mos)
Software Engineering - Associate (10 mos)
Software Engineering - Intern (1 yr 3 mos)
Chegg India
Subject Matter Expert - Software Development (7 mos)
Education
Master of Science - MS at Columbia University
Bachelor of Technology - BTech at Chitkara University
