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  1. Home
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  3. Nitesh Singhal
Nitesh Singhal's picture

Nitesh Singhal

Engineering leader building scalable AI/ML infra
Google
Country or state 
United States (California)
Available to 
Global
City 
San Jose
Fee 
Languages 
English
Volunteer
Yes
Timezone 
America/Los_Angeles

Personal Details

Bio

Nitesh Singhal is a technical leader with over 12 years of experience at Google, Uber, and Microsoft. He specializes in large-scale AI/ML infrastructure and distributed systems, with a track record of architecting real-time machine learning pipelines that handle millions of events per second at sub-second latency. In his career, he has directed technical strategy and delivered production-grade ML systems that power services ranging from real-time analytics to security-critical AI.

Beyond his technical accomplishments, Nitesh created and scaled an engineering excellence program that helped teams adopt stronger practices, ship with higher quality, and collaborate more effectively across the organization. He is also a regular speaker and technology awards judge, and he provides strategic advice to early-stage startups based on his extensive industry experience.

https://niteshsinghal.me/

Email:

nitesh@niteshsinghal.me

Current position (1)

Engineering leader building scalable AI/ML infra

Google

Degrees (1)
Computer Science
Indian Institute of Technology, Guwahati
2010 to 2014

Presentations

Presentations (3)
Designing Real-Time ML Pipelines at Scale

Lessons from building systems that process millions of events/sec with sub-second latency.

Scaling Data Platforms for AI

Patterns to build reliable, cost-efficient data platforms powering ML at global scale.

From Models to Production: ML Infra Lessons

Hard-won insights on deploying, monitoring, and operating ML models in real-world systems.

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Expertise (8)

Technology
Leadership
Artificial Intelligence Machine Learning Machine Vision Technical Leadership Technology StartUps Software Engineering
Recommendations
Why choose me? 

I make large-scale AI/ML simple and usable -- so your audience leaves with ready-to-apply tools.

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