About

About

Background

Hi! I am Rishabh Sood, a highly motivated Software Developer / ML Engineer with a solid foundation in the field of Computer Science. Having garnered valuable experience through internships at both Apple and Goldman Sachs, I currently contribute my skills as a Software Engineer at Apple. My expertise spans across the dynamic domains of Machine Learning, Artificial Intelligence, backend development and DevOps. Passionate about delivering swift, cost-effective technology solutions, I thrive on navigating new challenges in the ever-evolving landscape of computer science. With a steadfast mission to continually enhance my skills and contribute to groundbreaking technology, I am open to networking and enthusiastic about collaborating on future innovations in the tech industry.

Career

Apple
Machine Learning Engineer
Apple • Jan 2024 - Present
  • Support App Chat (Generative Experience): Engineered a generative multi-turn conversational AI for millions of users, featuring tool invocation and response validation.
    • Architected a multi-agent orchestration layer that reduced p95 latency by 75% by replacing rule-based agents with a fine-tuned Qwen-14B model.
    • Engineered a production-grade RAG pipeline with a focus on correctness and hallucination mitigation.
    • Implemented safety and policy enforcement layers.
  • Apple Developer Search: Led geographical expansion and optimized storage costs by 90% (10x reduction) using Solr/OpenSearch.
  • Knowledge Hub: Architected a centralized ETL pipeline (MQs/APIs → Cleaning & Embedding → Vector/Graph DBs).
Tech Stack: Python, LLM Fine-tuning (Qwen), RAG, GraphRAG, LangChain, Textgrad, MCP, Knowledge Graphs, FastAPI, Solr, OpenSearch, Neo4J, Docker
Goldman Sachs
Analyst
Goldman Sachs • Jul 2023 - Dec 2023
  • Infrastructure Migration: Designed and implemented components for a Kubernetes-based migration of the central App Store.
  • Data Aggregator: Architected a system to automate Kubernetes job scheduling for data lake onboarding, reducing manual overhead.
Tech Stack: Java, Spring Boot, Kubernetes, Docker, GitLab CI/CD, Gherkin, Cypress
Apple
Software Development Engineer (Intern)
Apple • Jan 2023 - Jun 2023
  • Intelligent Recommendation Service: Developed a service that reduced response time from minutes to sub-second latency.
  • Integrated generative responses and sentiment analysis.
  • Created a centralized Python package to reduce code redundancy.
Tech Stack: Python, PyPI Packaging, FastAPI, MongoDB, OpenSearch, Solr, Amazon EKS
Goldman Sachs
Summer Analyst (Intern)
Goldman Sachs • Jun 2022 - Jul 2022
  • Emergency Notification Service: Developed a global notification service, replacing a third-party vendor and saving USD 35-40K/annum.
  • Designed the system for easy extensibility.
Tech Stack: Golang, Kubernetes, Prometheus, Grafana, BigQuery, Docker

Education

Georgia Tech
M.S. Computer Science, Machine Learning Specialization
Georgia Institute of Technology • 2025 - Present
GPA: 4.0/4.0
Thapar Institute
B.E. Computer Science & Engineering
Thapar Institute of Engineering & Technology • July 2019 - June 2023
GPA: 9.92/10.0

Resume

Refer to Linkedin or pdf.