Hi, I'm Deep Rathi - AI Engineer @ Key | Ex‑ML Intern @ Remasto | Low‑Latency ML & Trading Systems | Generative AI | Real‑Time Inference & Optimization
I'm driven by building AI systems that perform at the edge, where every microsecond counts. I thrive on transforming complex research into production-grade solutions that deliver tangible value and push the boundaries of real-time inference.
At a glance
Curated signals on strengths, focus areas, and how they can help.
Led low-latency ML development for critical trading systems at Remasto.
Building high-performance generative AI for real-time inference at Key.
Can provide expertise on optimizing production AI systems for speed and efficiency.
🚀 Career trajectory
Foundational Research & Data Science
Early career experiences focused on fundamental research in deep learning, particularly for autonomous driving, and developing data-driven solutions through data science internships.
✦ Deep Learning
✦ Data Analytics
✦ Research
✦ Data Dashboards
Applied Machine Learning & Optimization
Transitioned to practical application of machine learning, focusing on building and optimizing generative AI models for real-time inference and low-latency systems.
✦ Generative AI
✦ Low-Latency Systems
✦ ML Pipelines
✦ Model Optimization
Advanced AI Engineering
Current role as an AI Engineer, leveraging comprehensive skills to develop and deploy advanced generative AI solutions and high-performance ML systems.
✦ AI Engineer
✦ Real-Time Inference
✦ Production ML
✦ System Design
💪🏻 Superpowers
Low-Latency ML & System Optimization
Expertise in designing and deploying high-performance machine learning solutions where speed is paramount.
✦ Optimized generative AI models for real-time inference.
✦ Developed low-latency trading systems, microseconds matter.
✦ Automated ML pipeline tasks for production efficiency.
Generative AI & Deep Learning Implementation
Hands-on experience developing and deploying cutting-edge generative AI models and deep learning applications.
✦ Built generative AI models for real-time deployment.
✦ Contributed to deep learning for autonomous driving.
✦ Applied AI research across multiple domains.
Production-Grade AI Engineering
Ability to bridge the gap between AI research and scalable, real-world production systems.
✦ Transformed AI concepts into production-grade systems.
✦ Automated ML pipeline for seamless deployment.
✦ Delivered data-driven solutions for operational improvements.
