Member of Technical Staff Intern

Role Overview

As an Researcher Engineer Summer Intern, you will join our core AI team to explore, design, and implement state-of-the-art machine learning models and LLM-driven architectures. You will work directly on the intelligence layer powering "Computer." This role bridges the gap between bleeding-edge AI research and production-ready features that impact thousands of users globally.

Key Responsibilities

• Algorithm Development & Experimentation: Research and implement novel techniques in agentic AI workflows, hybrid search (combining keyword and semantic retrieval), and Large Language Model (LLM) reasoning and memory management.
• Knowledge Graph Integration: Develop methodologies to improve how LLMs interact with DevRev’s enterprise knowledge graphs, moving beyond traditional RAG (Retrieval-Augmented Generation) approaches.
• Data Pipelines & Evaluation: Design robust evaluation frameworks to measure accuracy, latency, and relevance for semantic indexing, reranking pipelines, and our core answering engine.
• Collaborative Research: Partner with software engineers, product managers, and senior researchers to deploy models and algorithms into real-world production environments.
• Knowledge Sharing: Summarize and present research findings, literature reviews, and prototype results to engineering and leadership teams.

Learning Goals & Objectives

• Advanced LLM Training: Gain hands-on experience training, fine-tuning, and evaluating LLMs on complex, multimodal enterprise data.
• Architectural Mastery: Understand the underlying architecture of semantic search pipelines and agentic workflows at scale.
• Research Translation: Learn how to translate academic AI research into scalable, low-latency enterprise software.
• Communication: Develop professional skills by presenting complex AI concepts to both technical and non-technical stakeholders.

Qualifications

• Education: Currently enrolled in a Ph.D. program (second year or beyond) OR a Master’s degree with 4+ years of experience in Computer Science, AI, Machine Learning, Data Science, or a related quantitative field.

Required Skills:

• Programming: Strong proficiency in Python and ML frameworks (e.g., PyTorch, TensorFlow).
• AI Foundations: Solid knowledge of NLP, Deep Learning, and Information Retrieval.
• LLM Expertise: Experience with Large Language Models, prompt engineering, or vector embeddings.
• Execution: A track record of independent research or impactful academic/industry projects.

Desired Qualifications (Bonus)

• Publications in top-tier AI/ML conferences (NeurIPS, ACL, EMNLP, ICML, etc.).
• Experience with knowledge graphs, SQL-native data layers, or building autonomous AI agents.
• Active contributions to open-source AI projects.

What We Offer

• Mentorship: 1:1 pairing with a senior researcher.
• Impact: Direct influence on the capabilities of "Computer"; your work will be deployed in production.