Hi, I'm Deep Rathi - AI Engineer at Key
I am fueled by the challenge of making AI move at the speed of thought. My passion lies in engineering performance-critical systems that push technological boundaries, where I thrive in technical environments.
At a glance
Curated signals on strengths, focus areas, and how they can help.
Conducted high-impact applied AI research for autonomous driving systems during earlier tenure.
Currently building high-performance generative AI models and optimizing real-time inference pipelines at Key.
Provides technical expertise in C++, multithreading, and systems optimization to accelerate model deployment.
🚀 Career trajectory
Foundational Research
Explored applied AI research and data science internships to master core machine learning algorithms.
✦ Research Intern
✦ Data Science
Systems Engineering Specialization
Transitioned into high-performance computing, focusing on real-time inference and low-latency trading infrastructure.
✦ ML Intern
✦ C++ Specialist
AI Engineering Leadership
Currently scaling generative AI systems to production environments as a core AI Engineer.
✦ AI Engineer
✦ Generative AI
💪🏻 Superpowers
Systems Optimization Expert
Driving performance in high-stakes technical environments.
✦ Architects ultra-efficient low-latency trading and inference pipelines.
✦ Reduces computational overhead using C++ and multithreading strategies.
✦ Engineers production-grade systems that prioritize microsecond-level speed.
Generative AI Applied Researcher
Bridging cutting-edge models and real-world deployment.
✦ Integrates LLMs into scalable architectures using LangChain workflows.
✦ Refines real-time inference engines for generative AI applications.
✦ Transforms complex research into actionable, high-impact software solutions.
Autonomous Systems Analyst
Deep technical investigation of complex problem spaces.
✦ Conducts rigorous applied AI research within autonomous vehicle domains.
✦ Analyzes statistical datasets to enhance model accuracy and predictive speed.
✦ Uncovers system bottlenecks through intensive data visualization techniques.
I'm excited about
✦ Exploring advanced architectural patterns for large-scale generative AI deployments.
✦ Connecting with technical founders building the next generation of performance-critical tools.
✦ Identifying collaborative research opportunities to push the boundaries of real-time machine learning.
I can help with
✦ Advising teams on optimizing existing LLM inference pipelines for reduced latency.
✦ Mentoring early-career engineers on building robust, thread-safe C++ trading systems.
✦ Helping startups translate complex machine learning research into efficient, production-grade code.
I would love your help on
✦ Learning best practices for scaling internal AI infrastructure within high-growth startups.
✦ Gaining deeper insights into the current market landscape for real-time generative AI tools.
✦ Finding mentors who have successfully navigated the transition from research to systems engineering.