Ruchin Dhama
Verified Expert in Engineering
Machine Learning Engineer and Developer
Bengaluru, India
Toptal member since June 24, 2026
Ruchin is a senior machine learning engineer with over five years of experience in recommendation systems and generative AI for companies including Walmart and Samsung. He achieved up to 40% efficiency gains and a 4 – 5% total return on advertising spend at Walmart by deploying production-scale machine learning solutions. His expertise spans TensorFlow, PyTorch, and AWS for the retail and advertising industries.
Portfolio
Experience
- Recommendation Systems - 5 years
- Machine Learning - 5 years
- Python 3 - 5 years
- Generative Artificial Intelligence (GenAI) - 5 years
- SQL - 5 years
- PySpark - 5 years
- Retrieval-augmented Generation (RAG) - 5 years
- Agentic AI - 3 years
Preferred Environment
AWS IoT, Azure, Google Cloud Platform (GCP), Docker, Terraform, Jenkins, Apache Airflow, Recommendation Systems, Retrieval-augmented Generation (RAG), Python
The most amazing...
...recommendation system I've built delivered a 4 – 5% total return on advertising spend uplift at Walmart.
Work Experience
Software Development Engineer 3 | Machine Learning Engineer
Walmart Global Tech
- Designed and deployed a production end-to-end machine learning ranking and serving system for Walmart's sponsored ads platform, delivering 4 – 5% advertiser tROAS uplift and directly growing platform ad revenue.
- Productionized and maintained daily click and impression forecasting pipelines, reducing forecast error by approximately 10% across $5+ million in managed ad spend.
- Engineered an unsupervised detection system combining Shannon entropy and probabilistic click modeling to flag anomalous sessions in real time, mitigating bot traffic that was corrupting engagement KPIs.
- Built two production GenAI systems, including a large language model-based audience ID recommender and an agentic catalog chatbot with contextual ad insertion, reducing campaign setup time by approximately 40%.
Senior Engineer
Samsung R&D Institute India (SRIB)
- Architected the end-to-end SSP event ingestion pipeline from scratch across millions of events per hour, then optimized it to process 15-minute micro-batch windows, reducing data freshness from 24 hours to 15 minutes.
- Implemented frame similarity clustering to filter duplicate frames before Amazon Rekognition analysis, reducing API calls by approximately 40 – 50% and saving about $6,000 per year in Rekognition costs while maintaining coverage.
- Developed an LLM-powered data bot with SQL tool use that automated approximately 80% of recurring manual stats extraction tasks, delivering near-instant responses to queries that previously took hours.
- Conducted PySpark-based analysis across months of ad-serving event logs, identified failed acknowledgment callbacks from advertiser endpoints as the primary source of metric discrepancies, and shipped an automated reconciliation check to production.
Machine Learning Engineer
Travash Software
- Owned end-to-end machine learning delivery for three products: speaker recognition (audio embeddings), NLP resume parser (greater than 90% entity accuracy), and medical image segmentation (U-Net), enabling Travash to win follow-on contracts.
- Managed end-to-end project, including client communication and defining application architecture.
- Collaborated with cross-functional teams, enhancing performance and integrating trained models into the application.
Data Science Intern
VerSe Innovation
- Contributed to NLP and computer vision projects by performing data cleaning, feature engineering, and visualization across real-world content datasets.
- Tracked metrics like views, clicks, watch time, retention, shares, and CTR.
- Built simple reports and dashboards for the product or content team.
Experience
Text-to-image Generation
https://github.com/ruchind159/text_to_imageFace Mask Detection and Social Distancing Monitoring System
https://github.com/ruchind159/MaskDetectionConcrete and Pavement Crack Detection Using Deep Learning
https://github.com/ruchind159/crack_detectionEducation
Bachelor's Degree in Computer Engineering
Dr. D.Y. Patil School of Engineering (DYPSOE) - Pimpri-Chinchwad, India
Certifications
Build Basic Generative Adversarial Networks (GANs)
DeepLearning.AI | via Coursera
DeepLearning.AI TensorFlow Developer
DeepLearning.AI | via Coursera
Getting Started with AWS Machine Learning
AWS | via Coursera
Deep Learning Specialization
DeepLearning.AI | via Coursera
Data Science Math Skills
Duke University | via Coursera
Skills
Libraries/APIs
PySpark, PyTorch, Keras, Pandas, OpenCV, NumPy, Scikit-learn, Beautiful Soup, REST APIs, API Development, TensorFlow, Spark ML, XGBoost, LSTM, SciPy, OpenAPI, Hugging Face Transformers, Node.js, Google API, Google Places API
Tools
Git, GitHub, BigQuery, Visual Language Models (VLMs), Claude, Azure Machine Learning, AI Prompts, ChatGPT, ARIMA, Terraform, Jenkins, CVS, Flink, Apache Sqoop, Oozie, Microsoft Power BI, You Only Look Once (YOLO), Apache Airflow
Languages
SQL, Snowflake, Python, Python 3, Regex, C++, Java, JavaScript, TypeScript, R
Frameworks
Flask, LightGBM, Hadoop, Django, LangGraph, Agentic Frameworks, LlamaIndex, Data Lakehouse
Paradigms
ETL, Model Context Protocol (MCP)
Platforms
Amazon Web Services (AWS), AWS IoT, Azure, Google Cloud Platform (GCP), Docker, Apache Kafka, Databricks, Vertex AI, Kubernetes, LangSmith, Kubeflow, CrewAI, NVIDIA CUDA
Storage
PostgreSQL, MySQL, Databases, Data Pipelines, Data Lakes, Apache Hive, Database Management Systems (DBMS), Google Cloud Storage, Neo4j
Industry Expertise
Applied Statistics
Other
Generative Artificial Intelligence (GenAI), Large Language Models (LLMs), Natural Language Processing (NLP), Computer Vision, Recommendation Systems, Retrieval-augmented Generation (RAG), Deep Learning, Machine Learning, Data Science, AI Model Training, Time Series Forecasting, Image Processing, Artificial Intelligence (AI), Data Engineering, Datasets, API Integration, Data Analysis, Data Analytics, AI Modeling, Machine Learning Infrastructure Engineer, Data Visualization, Statistics, Time Series, Data Preprocessing, Large Data Sets, Statistical Analysis, Amazon Bedrock AgentCore, FastAPI, Communication, Feature Engineering, Linear Regression, Stakeholder Management, Decision Trees, Documentation, Web Scraping, Regression, Applied AI, Hugging Face, Multimodal Models, Open Weights, Geometry, Conversational Agent, System Architecture, Data Scientist, Agentic RAG Systems, Prompt Engineering, Semantic Search, Technical Leadership, Software Architecture, Machine Learning Operations (MLOps), AI Chatbots, Image Generation, Cloud, Software Engineering, Architecture, CI/CD Pipelines, Back-end, Back-end Development, APIs, Classification, Data Extraction, Optical Character Recognition (OCR), Google BigQuery, Infrastructure as Code (IaC), OpenAI, PDF, PDF Scraping, Machine Learning (ML) APIs, Sentiment Analysis, AI Engineering, LLM Integration, Distributed Systems, Product Engineering, Attention to Detail, Code Review, Written Communication, Interviewing, AI Systems, U-Net, Kafka, Paper review, AI Agents, Agentic AI, Forecasting, Big Data, Signal Analysis, Generative Adversarial Networks (GANs), Neural Networks, Time Series Analysis, Fine-tuning, Applied Mathematics, Image Analysis, Transfer Learning, Model Evaluation, Algorithms, Finance, Quantitative Modeling, Azure Databricks, Chatbots, Financial Modeling, Demand Forecasting, Model Deployment, Model Development, Monitoring, Random Forests, Causal Inference, LLM Fine-tuning, LLM Reasoning, Reinforcement Learning, Vector Databases, Video Analysis, IT Strategy, Azure Cognitive Search, LoRa, LangChain, Integration, Modeling, Financial Data, Fraud Detection, Fraud Prevention, Large Language Model Operations (LLMOps), Agentic Workflow Design, RAG Architecture, RAG Systems, Agentic AI Systems, Scalable Vector Databases, Anthropic, Text-to-Speech (TTS), Predictive Modeling, Observability, Solution Architecture, AWS Cloud Architecture, Cloud Architecture, Analytics, Sequence Models, Transformers, Consulting, Data-informed Recommendations, IT Consulting, Evaluation, Document Processing, AI Agent Orchestration, Conversational AI, Workflow Automation, Speech-to-Text (STT), Multi-agent Systems, MLflow, Multi-tenant SaaS, Team Leadership, Screeners, Derivatives, Probability Theory, Calculus, Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), Real-Time Video Analytics, Object Detection, Image Segmentation, Structural Health Monitoring, Pattern Recognition, Data Annotation, Trading, Bayesian Statistics, Knowledge Graphs, OpenAI SDK, Multi-agent Orchestration, RAG Pipelines, Active Learning, Predictive Learning, Performance Optimization, Data Build Tool (dbt), Web Development, Web Applications, Amazon Redshift
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