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I’m an AI/ML engineer with 3+ years of experience, a Master’s in Data Science from the University of Colorado Boulder, and a B.Tech from IIT Kharagpur. I build AI agents, RAG pipelines, and LLM-driven applications with proven expertise in LangChain, vector databases, and multi-agent orchestration. I enjoy delivering scalable AI/ML solutions across domains like real estate, scientific research, and ecological monitoring, and I’m actively seeking opportunities to create innovative AI systems that bridge cutting-edge research with real-world business impact.…I’m an AI/ML engineer with 3+ years of experience, a Master’s in Data Science from the University of Colorado Boulder, and a B.Tech from IIT Kharagpur. I build AI agents, RAG pipelines, and LLM-driven applications with proven expertise in LangChain, vector databases, and multi-agent orchestration. I enjoy delivering scalable AI/ML solutions across domains like real estate, scientific research, and ecological monitoring, and I’m actively seeking opportunities to create innovative AI systems that bridge cutting-edge research with real-world business impact.

Lalit Sai Reddy Kamala Lalith Kamala

Data Analyst, AI Engineer, Data Scientist, +7

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I’m an AI/ML engineer with 3+ years of experience, a Master’s in Data Science from the University of Colorado Boulder, and a B.Tech from IIT Kharagpur. I build AI agents, RAG pipelines, and LLM-driven applications with proven expertise in LangChain, vector databases, and multi-agent orchestration. I enjoy delivering scalable AI/ML solutions across domains like real estate, scientific research, and ecological monitoring, and I’m actively seeking opportunities to create innovative AI systems that bridge cutting-edge research with real-world business impact.…I’m an AI/ML engineer with 3+ years of experience, a Master’s in Data Science from the University of Colorado Boulder, and a B.Tech from IIT Kharagpur. I build AI agents, RAG pipelines, and LLM-driven applications with proven expertise in LangChain, vector databases, and multi-agent orchestration. I enjoy delivering scalable AI/ML solutions across domains like real estate, scientific research, and ecological monitoring, and I’m actively seeking opportunities to create innovative AI systems that bridge cutting-edge research with real-world business impact.

Available to hire

I’m an AI/ML engineer with 3+ years of experience, a Master’s in Data Science from the University of Colorado Boulder, and a B.Tech from IIT Kharagpur. I build AI agents, RAG pipelines, and LLM-driven applications with proven expertise in LangChain, vector databases, and multi-agent orchestration.

I enjoy delivering scalable AI/ML solutions across domains like real estate, scientific research, and ecological monitoring, and I’m actively seeking opportunities to create innovative AI systems that bridge cutting-edge research with real-world business impact.

Skills

Experience Level

Expert

Expert

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Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

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Expert

Intermediate

Intermediate

Intermediate

Intermediate

Intermediate

Language

English

Fluent

Work Experience

AI/ML Engineer at ZONZON INC

July 1, 2025 - August 21, 2025

Developed GPT-powered conversational flows and data pipelines from chatbot interactions to drive personalized user onboarding and engagement strategies. Led end-to-end development of a GPT-powered assistant embedded in the platform to automate onboarding and personalize group interactions. Designed adaptive onboarding pipelines generating group-specific messages using user metadata and behavioral cues. Demonstrated expertise in machine learning model development, training, evaluation, and deployment. Utilized MySQL for analysis and dashboard creation to support strategic business planning. Developed and maintained robust Python applications improving system performance by 25%. Created interactive dashboards and reports in Power BI enabling real-time business insights. Integrated NLP, large language models, and multimodal AI technologies into product features. Managed project workflows using Jira to coordinate chatbot development and user engagement initiatives. Designed, developed, and

Data Scientist - AI/ML at University of Colorado Boulder - Lambert Lab

May 1, 2025 - August 21, 2025

Enabled natural language search over scientific documents by transforming unstructured PDFs into vectorized, queryable formats and designing LLM-powered workflows for context-aware answers from research content. Developed a scalable AI assistant for natural language querying over academic research by combining document parsing, vector embedding, and large language model inference. Built end-to-end ETL pipelines to extract, clean, lemmatize, and segment raw PDF content using pypdf, regex, and custom NLP scripts; stored structured embeddings for 100+ page documents in Pinecone for semantic retrieval. Orchestrated data preprocessing workflows including text normalization, chunking, token counting using TikToken, and vector encoding with OpenAI’s text-embedding-ada-002 model. Deployed a modular Flask-based REST API server managing user sessions, document uploads, and chat interactions with robust error handling, retry logic, and session memory via Flask-Session and SQLAlchemy. Implemente

AI Software Engineer at GRIZLY SYSTEMS INC

January 31, 2025 - August 21, 2025

Enhanced wildlife monitoring by integrating species classification and thermal object detection models into field systems, streamlining data capture, preprocessing, and analysis for real-time ecological insights. Developed and maintained end-to-end data pipelines for ingesting, preprocessing, and formatting large-scale thermal imaging and wildlife camera datasets. Built scalable input pipelines using Python and NumPy to feed image streams into CNN-based inference models with minimal latency. Deployed modular AI components including object detection, species classification, and thermal anomaly detection into production-grade monitoring systems, improving tracking precision and increasing field team efficiency by 20% through automated alerts and smarter data routing. Conducted hyperparameter tuning and model optimization using TensorFlow and Keras achieving a 10% increase in classification accuracy. Applied efficient checkpointing, transfer learning, and early stopping to maintain perfor

Machine Learning Researcher at Indian Institute of Technology Kharagpur

May 1, 2023 - August 21, 2025

Enabled autonomous fruit harvesting by designing a two-stage vision system for occlusion-aware apple detection and monocular depth estimation using YOLOv7, EfficientNet-B0, and pix2pix GAN architectures. Developed a machine vision pipeline proposing a two-stage deep learning system that first detects apples using YOLOv7 object detection, followed by occlusion classification using EfficientNet-B0-based CNN. The system enabled real-time fruit localization and classification into occlusion categories (non-occluded, leaf-, stem-, fruit-occluded) to inform downstream end-effector grasp planning. Engineered a conditional Generative Adversarial Network (cGAN) for monocular RGB-to-depth estimation of apple orchards modeled using pix2pix architecture for image-to-image translation, translating RGB canopy images into dense depth maps with high fidelity. Achieved strong performance across depth prediction metrics with SSIM > 0.92, PSNR > 25dB, and RMSE = 1.833 cm supporting high-precision plannin

Data Science Intern at AI HELLO

June 1, 2022 - August 21, 2025

Improved e-commerce forecasting and product listing automation by building time series models, reinforcement learning agents, and image processing tools for Amazon marketplace data. Developed time series forecasting models using ARIMA to predict future sales trends of Amazon products based on historical marketplace data. Tuned hyperparameters and validated model performance across multiple product categories. Trained a reinforcement learning agent to forecast stock price movement using technical indicators: Moving Average (MA), MACD, and RSI. Evaluated agent behavior and convergence using reward-based learning simulations. Built a Python-based automation script for product image preprocessing that removes image backgrounds using a pre-trained MODNet. Optimized the pipeline for batch processing of product listings.

AI Consultant at Accenture

May 1, 2024 - Present

Client: Zonzon. Built Agile AI / Generative AI agents to streamline onboarding, outreach, sales, and marketing pipelines. Led development of agent architecture using LangGraph, integrated retrieval-augmented generation (RAG) with GPT models and vector databases to support onboarding and CRM workflows. Built scalable data pipelines in Python to scrub, clean, and transform large-scale web and enterprise data into structured formats for downstream AI/ML workloads. Designed modular multi-agent systems with dedicated agents for Home Finder, Contextual Research, Outreach, and Community Engagement, plus vendor integration and orchestration. Implemented multi-agent coordination and memory-aware prompt orchestration; deployed a production-grade RESTful API with caching and session memory for real-time interactions.

AI Software Engineer at Grizzly Systems Inc

January 31, 2025 - October 25, 2025

Enhanced wildlife monitoring by integrating species classification and thermal anomaly detection into field systems. Built end-to-end data pipelines for ingestion and processing of large-scale thermal imagery using Python and NumPy; developed monocular RGB depth estimation with YOLOv7 and EfficientNet-B0; deployed modular AI components for object detection, species classification, and thermal anomaly detection; achieved real-time inference and improved field deployment accuracy.

Data Scientist Intern at AI Hello

June 1, 2022 - October 25, 2025

Improved e-commerce forecasting by building time-series models (ARIMA) to predict future sales trends for Amazon products; tuned hyperparameters and validated model performance across multiple product categories. Trained a reinforcement learning agent to forecast stock price movements using MA, MACD, and RSI; evaluated agent behavior and convergence using reward-based simulations. Built a Python automation script for product image preprocessing that removes backgrounds using a pre-trained MODNet; optimized the pipeline for batch processing of product listings.

AI Consultant at Accenture

May 20, 2024 - Present

Built Agentic AI / Generative AI agents to streamline onboarding, outreach, and marketing processes; designed modular multi-agent architectures using LangGraph, RA G, LLMs, and vector databases; implemented scalable data pipelines in Python; led on onboarding, outreach, and CRM workflow automation for a remote client project.

AI Software Engineer at Grizzly Systems Inc

January 1, 2025 - October 25, 2025

Enhanced wildlife monitoring by integrating species classification and thermal object detection models into field systems; built end-to-end ML workflows; deployed modular AI components; integrated multi-modal inputs and metadata for adaptive dialogue and reporting; established scalable monitoring pipelines.

Machine Learning Researcher at Indian Institute of Technology Kharagpur

May 1, 2023 - October 25, 2025

Designed a two-stage vision system for occlusion-aware apple detection and monocular depth estimation using YOLOv7, EfficientNet-B0, and pix2pix GAN; built a Mach ine Learning pipeline for orchard depth maps; produced depth-calibrated data and integrated with growing robotics workflows.

AI Software Engineer at GRIZLY SYSTEMS INC

January 1, 2025 - October 25, 2025

Remote, USA. Led the development of Agent AI architecture using LangGraph, integrating Retrieval-Augmented Generation (RAG), LLMs (GPT, LLaMA), and vector databases to streamline onboarding, outreach, and marketing pipelines. Built scalable data pipelines in Python to scrape, clean, and transform large-scale web and enterprise data into structured formats for downstream AI/ML workloads. Designed modular multi-agent systems with dedicated agents for Home Finder, Contextual Research, Outreach, and Community Engagement, enabling focused task execution and human-like interactions. Implemented RAG pipelines with GPT-4 + Pinecone for context-aware generation, dynamic prompt routing, and fallback strategies, demonstrating scalable LLM-RAG capabilities. Orchestrated cross-LLM coordination using MCP patterns and context memory buffers for efficient long-horizon task execution. Enabled multimodal input handling across agents with metadata, text, and embeddings for adaptive dialogue and lead gene

Data Science Intern at AI Hello

June 1, 2022 - October 25, 2025

Remote, Canada. Enhanced e-commerce forecasting and product listing automation by constructing time series models (ARIMA) to forecast future sales trends across Amazon product categories. Tuned hyperparameters and validated model performance across multiple product categories. Trained a reinforcement learning (RL) agent to forecast stock price movement using indicators like Moving Average, MACD, and RSI, with simulations to evaluate behavior and convergence. Built a Python automation script for pre-processing product images and batch listing uploads, reducing manual processing time.

Machine Learning Researcher at Indian Institute of Technology Kharagpur

May 20, 2023 - October 25, 2025

Kharagpur, India. Enabled autonomous fruit harvesting by designing a two-stage vision system for occlusion-aware apple detection and monocular depth estimation using YOLOv7, EfficientNet-B0, and pix2pix GAN. Developed a monocular depth estimation model to generate dense depth maps for robotic grasp planning, achieving high fidelity (SSIM > 0.9, PSNR > 25 dB). Demonstrated real-time fruit localization and categorization (non-occluded, leaf-occluded, stem-occluded). Integrated pre- and post-processing pipelines for image normalization, occlusion-aware augmentation, and depth map calibration to preserve variety in lighting and foliage density. The work was published in Springer and presented at international conferences, illustrating practical applicability in agri-robotics and deep learning.

AI Consultant at Lambert Lab

January 1, 2025 - October 25, 2025

Client Lambert Lab. Enabled natural language search over scientific documents by transforming unstructured PDFs into vectorized, queryable formats and designing LLM-powered workflows for context-preserving responses. Implemented modular LLM pipelines for academic research querying, integrating RAG techniques and vector-based memory to support persistent, context-aware responses. Coordinated data upload, retrieval, summarization, and answer generation with discrete, auditable steps for debugging and compliance. Demonstrated end-to-end automation and orchestration across LLM components using 3rd-party platforms (Zillow, Clay, Apollo) to accelerate onboarding and engagement workflows.