Member of Technical Staff Intern

About DevRev

At DevRev, we're building the future of work with Computer – your AI teammate. Unlike traditional tools, Computer unifies all your data sources, tools, and workflows into a single AI-ready platform, giving employees real-time insights, proactive suggestions, and powerful agentic actions. It extends your existing software with AI-native apps and agents that work alongside your teams and customers – updating workflows, coordinating across teams, and eliminating repetitive work. We call this Team Intelligence: human-AI collaboration that breaks down silos, brings people back together, and frees you to solve bigger problems. Backed by Khosla Ventures and Mayfield with $150M raised, DevRev is trusted by global companies across industries.

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.
  
  

DevRev is an equal opportunity employer and does not discriminate on the basis of race, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition, or any other basis protected by law.