Summary
Overview
Work History
Education
Accomplishments
Timeline
Generic

Greeshma Yaluru

San Jose

Summary

Versatile Cloud Program Strategist with 5+ years orchestrating high-impact data and AI transformations across PNC Bank, Amazon, and MIT. Engineered Azure migration blueprints powering 20M+ users, pioneered GenAI risk intelligence systems with a 25% detection boost, and mobilized 5+ org units to drive factory-style analytics scale-ups. Known for harmonizing execution with vision — from prototype to production — while embedding stakeholder intent into every technical roadmap.

Overview

6
6
years of professional experience

Work History

Technical Lead, ML & Cloud Operations

PNC Bank
Pittsburgh
07.2024 - Current
  • Owned delivery of 7+ Azure-based machine learning pipelines, driving roadmap alignment, sprint planning, and program execution across engineering, infrastructure, and analytics teams.
  • Drove PoC-to-Production deployment for GenAI-based Risk Management RAG solution, improving document analysis speed by 25% and aligning delivery with cloud transformation KPIs.
  • Partnered with 5+ stakeholder groups (Data Engineering, Scheduling, Infra, Business Execs, Governance) to align scope, budget, timelines, and reporting for multi-phase Azure migration programs.
  • Reduced Azure deployment bottlenecks by coordinating stakeholder inputs, data load SLAs, and implementation schedules.
  • Orchestrated production deployment for real-time modeling across 20M+ users using Docker, Kubernetes, and CI/CD on Azure infrastructure.
  • Delivered all key milestones on schedule and under budget; reported progress to leadership and contributed to TPM best practices.
  • Conducted enablement sessions and evangelized scalable analytics solutions using Azure Synapse, Data Lake, and Data Factory.
  • Incorporated KPIs and customer feedback into technical roadmaps, aligning platform capabilities with business outcomes.
  • Led Cloud Accelerate Factory-style sessions internally; helped develop repeatable IP and assets for scalable analytics migration.

Researcher, AI/ML Division

MIT Research Lab
Boston
05.2023 - 07.2023
  • Co-developed Focused Concept Miner (FCM) using PyTorch and contrastive learning to boost concept coherence by 28% in NLP systems.
  • Implemented self-supervised and multimodal retrieval learning to increase semantic alignment by 25% on benchmark datasets.

Machine Learning Engineer

Altastata
Remote
01.2023 - 04.2023
  • Created ML models to predict digital subscription churn using PySpark and Azure Synapse Analytics.
  • Worked with cross-functional teams to define metrics, automate pipelines, and deliver dashboards for executive reporting.

Associate, Cloud & AI Division

Amazon
Hyderabad
02.2022 - 07.2022
  • Reduced fraud triage time by 35% through a GenAI-based anomaly detection dashboard; analyzed large AWS datasets using Athena, Lambda, Kinesis, and S3.
  • Cut $500K in yearly infra cost by streamlining high-velocity ETL pipelines and accelerating project timelines by ~3 months.

Lead, ML Ops & AI Systems

Trimindtech & SettleMetal
Hyderabad
04.2019 - 01.2022
  • Built ML pipelines using Azure ML, SageMaker, and Vertex AI, driving up to 15% revenue gains via personalization and forecasting models.
  • Enhanced risk reporting by 40% via vector search pipelines using OpenAI; reduced manual review by 60%.
  • Cut training costs by $300K annually by implementing distributed training on Kubernetes using TensorFlow, Horovod, and TFX.

Machine Learning Intern

Kolate AI
Remote
07.2021 - 11.2021
  • Developed PoC for B2B personalization using NLP and embedding models deployed via Azure Functions.
  • Assisted in customer success calls, gathering feedback to iterate on ML pipeline efficiency and explainability.

Education

Master of Science - Computer Science

Boston University, GRS Campus
Boston, MA
01-2024

Accomplishments

· Teaching Assistant, Advanced Deep Learning (Graduate Level) | Boston University (Sep 2022 – Dec 2022)
Supported 80+ students; improved assignment completion by 20%.

· CS Ambassador, BU GRS Campus (Jan 2022 – Dec 2022)
Mentored 50+ peers; increased program interest by 30% via conference outreach.

· Top 10 – Global AI Hackathon (Kaggle) (Mar 2022)
Outperformed 500+ teams; boosted F1 by 12% over baseline.

· Best Mobile App Winner – AI-powered application, 100+ entries (2023)

· Research Paper under review at NeurIPS 2025 – Contrastive Multimodal Embeddings

· Planned Submission to ICML 2025 – Goal-Based ML in AdTech (18% lift in revenue simulation)

Timeline

Technical Lead, ML & Cloud Operations

PNC Bank
07.2024 - Current

Researcher, AI/ML Division

MIT Research Lab
05.2023 - 07.2023

Machine Learning Engineer

Altastata
01.2023 - 04.2023

Associate, Cloud & AI Division

Amazon
02.2022 - 07.2022

Machine Learning Intern

Kolate AI
07.2021 - 11.2021

Lead, ML Ops & AI Systems

Trimindtech & SettleMetal
04.2019 - 01.2022

Master of Science - Computer Science

Boston University, GRS Campus

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Greeshma Yaluru