Krish Sharma

Experience

Roles, impact, and selected accomplishments

Cofounder and Chief Technical Officer

Valence Ledger • New York, NY / Miami, FL
June 2025 – Present
  • Engineered AI agents that automate MCA (Merchant Cash Advance) operations for 50+ brokers and private credit funds, reducing manual processing by 40% across intake, syndication, and payout workflows.
  • Integrated automated follow‑ups, legal assignment, and background checks to improve compliance workflow efficiency by 55% and accelerate merchant onboarding timelines by 30%.
  • Consolidated siloed MCA workflows (lead ingestion, syndicator management, client communications, underwriting) into a single platform, increasing deal close rates by 18%.
VC‑backed

Cofounder and Co‑Chief Technical Officer

Deployo.ai (Acquired) • Remote
Jan 2025 – July 2025
  • Pioneered a no‑code AI deployment platform enabling one‑click promotion from concept to production in seconds.
  • Engineered optimization algorithms to ensure optimal resource allocation for deployed models across cloud environments, reducing operational costs by up to 30%.
  • Contributed to a 5× increase in deployment speed compared to traditional methods, significantly accelerating time‑to‑market for AI‑powered applications.
VC‑backed

Technology Analyst Intern, Wealth Management

Morgan Stanley • Atlanta, GA
Jan 2025 – May 2025
  • Built AI‑driven portfolio optimization models that improved risk‑adjusted returns by 12% and accelerated decision support.
  • Integrated AI into financial data pipelines, increasing processing accuracy by 15% and reducing latency for real‑time analytics.
  • Streamlined onboarding and business acquisition workflows, cutting processing time by 20% to unlock faster client delivery.

Machine Learning Engineer Intern

Fung Group — Georgia Institute of Technology • Atlanta, GA
Jan 2024 – Present
  • Implemented Graph Neural Networks (PyTorch/TensorFlow) for materials science; achieved ~20% accuracy gains with pre‑training and tuning.
  • Prototyped crystal structure prediction and active learning for topology optimization to accelerate materials discovery.
  • Integrated inverse design with spectral analysis and GNNs, creating an end‑to‑end pipeline for AI‑assisted property prediction.
View my Resume