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GANESH JHA

@ganeshjha

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Staff machine learning engineer building scalable AI systems and production GenAI solutions.

United States

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What I'm looking for

I seek a role building production-scale ML/GenAI systems with strong engineering practices, cross-functional impact, and opportunities to influence product outcomes.

I am a results-driven machine learning engineer with deep experience building production AI and GenAI systems for high-scale consumer and enterprise applications. I combine strong foundations in C/C++, Python, data structures, and UNIX scripting with cloud and ML platform expertise to deliver reliable ML products.

At Microsoft I architected and productionized real-time hybrid recommender pipelines and GenAI auto-notes systems, achieving measurable business impact such as a 16% CTR lift and multi-million-dollar savings through improved processes. I emphasize robust deployment patterns, monitoring, RAI/DSB compliance, and multi-region high-availability.

My background spans end-to-end ML lifecycle work — from research and prototype to large-scale production — across recommendation, scoring, and forecasting problems. I have published research on GAN-based data augmentation and worked on deep learning projects for signal and image domains.

I seek to apply my engineering rigor and product-minded ML expertise to build scalable, cost-effective AI solutions that drive user value and measurable business outcomes.

Experience

Work history, roles, and key accomplishments

Current

Staff ML Engineer

Current

Credit Com LLC

Nov 2025 - Present (2 months)

Design, develop and scale machine learning systems powering AI-driven consumer experiences, including intelligent agents for customer interaction and financial automation.

Machine Learning Agentic AI Python C++MLOps Prompt Engineering

Senior Data & Applied Scientist

Microsoft

Aug 2022 - Oct 2025 (3 years 2 months)

Architected and productionized real-time hybrid recommender and GenAI systems handling 300 RPS with <200ms latency, driving a 16% CTR lift and reducing co-sell referral expiry to 10%, saving ~$107M annually.

Recommender Systems Azure OpenAI Embeddings Python A B Testing MLOps

Senior Data Scientist

Publicis Groupe

Dec 2019 - Jul 2022 (2 years 7 months)

Built scalable marketing ML models including churn and CLV prediction and a deep collaborative filtering recommender achieving 81% hit rate and 60% NDCG to improve campaign targeting.

Customer Segmentation Deep Learning MLFlow Spark Python

Machine Learning Software Engineer

Cadence Design Systems

Jul 2019 - Dec 2019 (5 months)

Applied ML and deep learning techniques to EDA tools, replacing heuristic power-optimization methods with ML models to improve runtime and prediction performance.

C++Python Deep Learning Performance Optimization Model Inference Runtimes MLPack

Deep Learning Research Assistant

California State University, Fresno

Sep 2018 - May 2019 (8 months)

Researched GAN-based data augmentation and 3D CNN architectures for ERP detection, resulting in conference and journal publications improving handwritten digit recognition and ERP classification.

Python Research

Software Engineer (C++/Python)

Cadence Design Systems

Oct 2015 - Jan 2018 (2 years 3 months)

Developed compiler and RTL tooling features in C++, adding semantic checks and automated logical equivalence checking flows with unit tests and regression analysis.

C++Compiler Development RTL Unit Testing regression Tooling