Chaitanya Patil

Chaitanya Patil

Senior ML engineer. Production systems across real-time ML, agentic GenAI, and applied research.

Brisbane, QLD · Australia

01

About

I build production ML systems. I’ve worked on real-time ad decisioning, applied research on acoustic-scene monitoring, and most recently agentic GenAI for clinical research at Gilead Sciences.

M.S. from UC San Diego, where I was co-advised by Peter Gerstoft and Yoav Freund. AWS ML Certified.

Currently working with

Amazon Bedrock LangGraph LangChain FastAPI PyTorch RAG Python AWS
02

Experience

Oct 2025 – Present Remote · Client: Gilead Sciences

Senior Software Engineer, GenAI

UsefulBI Corporation

  • Maintained and extended a multi-agent Text-to-SQL system at Gilead that lets clinical analysts query trial data in natural language. Added multimodal visual QA that regenerates code when rendered charts fail validation, plus self-correcting retry loops in the visualization agent.
  • Rewrote the data onboarding pipeline, fixed a diversity-of-results issue in the real-world data (RWD) agent, and diagnosed intermittent frontend-backend disconnections (resolved with exponential-backoff reconnection).
  • Owned the GenAI side of an internal medical writing tool for Clinical Study Report generation, which I scaled to support other regulatory document types. Tripled document length from 30 to 100 pages, improved table and image formatting, added per-paragraph citations, and built an automated template generation feature on top of the existing template-based flow.
  • Added LLM-as-a-judge QC for generated content, per-section regeneration, and page-number filtering in OpenSearch retrieval.
  • Led cross-functional delivery across engineering, data scientists, and pharma subject-matter experts. A lot of the work was translating requirements between these groups.
Aug 2021 – Sep 2025 Austin, TX · USA

Machine Learning Engineer

Decide Technologies Inc.

  • Shipped a 100× reduction in inference latency on a revenue-critical ad-decision engine, unblocking real-time bidding at production scale. Approach: JIT-compiled the inference path with Numba; rewrote the hot loop for cache efficiency.
  • Owned the team-wide model evaluation pipeline: one reusable framework adopted across every ML project, replacing ad-hoc per-model scripts.
  • Built a parallelised execution system using multiprocessing for 4×+ speedup in model evaluation.
  • Designed and deployed four ad-selection models reaching top-quartile performance, integrated into containerised CI/CD pipelines with Docker and GitHub Actions.
Jun 2020 – Jul 2021 La Jolla, CA · USA

Data Science Researcher

Scripps Institution of Oceanography, UC San Diego · co-advised by Peter Gerstoft & Yoav Freund

  • Research under Peter Gerstoft and Yoav Freund on acoustic-scene monitoring: using ad hoc microphone arrays to localize sound sources in indoor environments.
  • Built data pipelines for cleaning and storing sensor data, and authored a Python analysis library used across the research group.
  • Applied Principal Component Analysis and regression models to recover source locations from raw audio. Migrated sensor data infrastructure from Google Drive to MySQL for 100× faster preprocessing.
  • Work contributed to a peer-reviewed paper in the IEEE Internet of Things Journal (March 2022).
Apr 2020 – Jun 2021 San Diego, CA · USA

Graduate Teaching Assistant

University of California, San Diego

  • TA for DSC 100: Introduction to Data Management (Winter & Spring 2021). Led sections on SQL, relational modeling, and data wrangling.
  • Tutor for ECE 15: Intro to Programming in C (Fall 2020). Supported undergraduate students with fundamentals of systems programming.
  • TA for PHYS 1AL: Mechanics Laboratory (Spring 2020).
Jul 2018 – Dec 2018 Pune, India

Signal Processing Intern

Wavelet Group

  • Developed a radar signal processing algorithm for calculating the distance, speed, and angle of approach of moving objects.
  • Synthesized and validated the algorithm on an FPGA.
  • Built a Python GUI for real-time visualization of approaching objects.
03

Selected Projects

Resume RAG Chatbot

Retrieval-augmented chatbot using OpenAI embeddings, FAISS indexing, and a FastAPI backend. Deployed with CORS hardening, health checks, and token/latency logging, optimized for cost within free-tier constraints.

RAGFAISSOpenAIFastAPIPython

Time Series Caption Generator

Neural captioning model using CNN + LSTM in PyTorch with a custom noun-weighted loss function. Received top grade and recognition for novelty and rigor.

PyTorchCNNLSTMNLP

Instacart Recommender System

Collaborative filtering system with TF-IDF weighting, popularity adjustments, and product-category enrichment for personalized item recommendations.

Recommender SystemsTF-IDFPython
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Education

M.S. Electrical Engineering
University of California, San Diego
2019 – 2021
Statistical Learning · Data Structures · Algorithms · Deep Learning for Computer Vision · NLP · Database Management
B.Tech. Electronics Engineering
University of Pune
2015 – 2019
06

Awards & Honors

Government of Maharashtra Scholarship for Higher Education in Foreign Countries

Government of Maharashtra, India · Awarded for graduate studies at UC San Diego

A competitive state-government scholarship supporting students from Maharashtra pursuing postgraduate studies abroad, awarded on the basis of academic merit.

Runner-Up: Best Outgoing Student

University of Pune · B.Tech. Electronics Engineering

Recognized for overall academic excellence and contribution at the undergraduate level.

English Proficiency: Perfect Scores

PTE Academic 90/90 (2025) · TOEFL 120/120 (2018)

Perfect scores on both major standardized English proficiency exams.

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Skills

GenAI & LLMs

Agentic Workflows LangChain LangGraph RAG FAISS Prompt Engineering LLM Evaluation Multi-Model Orchestration Amazon Bedrock OpenAI API

📈 ML & Data Science

PyTorch TensorFlow Keras Scikit-Learn CatBoost Pandas NumPy Matplotlib Recommendation Systems Real-Time Inference

Cloud & Infrastructure

AWS Bedrock SageMaker S3 Redshift DynamoDB OpenSearch GCP BigQuery Pub/Sub Docker CI/CD GitHub Actions

💻 Languages & Tools

Python JavaScript SQL C FastAPI Uvicorn REST APIs Linux Git Numba Multiprocessing
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Let’s talk

Open to conversations about production ML, agentic system design, or senior ML/AI hires. The fastest way to reach me is email. I reply to everything.

patilchait@gmail.com