Hi, I'm Deep Rathi - AI Engineer at Key
I am driven by the thrill of turning chaotic data into intelligent, seamless systems. I thrive in high-stakes environments where rapid experimentation meets rigorous engineering to solve the hardest problems.
At a glance
Curated signals on strengths, focus areas, and how they can help.
Built foundational machine learning architectures at Key to scale predictive data infrastructure.
Engineers advanced AI solutions that bridge the gap between complex theoretical research and real-world application.
Offers technical mentorship on scaling artificial intelligence systems and navigating the transition from prototype to production.
🚀 Career trajectory
Foundational Research
Explored academic applications of data science and AI modeling through internships.
✦ Research Intern
✦ Data Analytics
System Engineering & ML
Transitioned into high-stakes development, focusing on real-time inference and optimization at the industry level.
✦ AI Engineer
✦ Low-Latency
💪🏻 Superpowers
Latency Architect
Engineering performance in time-critical systems
✦ Optimizes real-time inference for high-speed generative AI models.
✦ Engineers low-latency trading systems to resolve microsecond bottlenecks.
✦ Applies multithreading and C++ to maximize system throughput.
AI Implementation Specialist
Translating research into robust production environments
✦ Deploys scalable machine learning models using PyTorch and TensorFlow.
✦ Integrates LangChain and LLMs into live production-grade applications.
✦ Converts experimental AI research into functional, scalable software.
Data Infrastructure Strategist
Designing high-availability data architectures
✦ Designs data structures for large-scale analytics and reporting.
✦ Leverages AWS and SQL to create reliable data management flows.
✦ Analyzes statistical patterns to drive architectural decision-making.
I'm excited about
✦ Exploring advancements in high-frequency trading and low-latency AI architectures.
✦ Connecting with experts to exchange knowledge on production-level ML challenges.
✦ Identifying collaborative opportunities to build next-generation real-time inference engines.
I can help with
✦ Consulting on optimizing existing ML pipelines for lower latency.
✦ Mentoring junior developers on C++ applications in data-intensive environments.
✦ Advising teams on the deployment of Generative AI at scale.
I would love your help on
✦ Learning best practices for scaling production-grade AI infrastructure.
✦ Finding mentors specializing in ultra-low-latency distributed computing systems.
✦ Identifying new communities focused on AI-driven financial technology.