Nitesh Singhal

CTO

San Francisco, California, United States12 yrs 3 mos experience

Most Likely To SwitchAI ML Practitioner

Key Highlights

Expert in building AI/ML infrastructure.
Keynote speaker and tech-awards judge.
Proven track record in scaling teams and organizations.

Stackforce AI infers this person is a leader in AI/ML infrastructure and distributed systems.

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Skills

Core Skills

Artificial IntelligenceDistributed SystemsStream ProcessingData Platform

Other Skills

AI AgentsAlgorithmsApache AirflowApache DruidApache FlinkApache KafkaApache PinotApache SparkApache ZooKeeperArchitectureAresDBC#C++CoachingCode Review

About

Engineering leader focused on AI/ML infrastructure, generative-AI platforms, and large-scale distributed systems. I build production-grade ML infra that increases velocity and reliability, and scale teams and orgs. Keynote speaker at industry events and regular tech-awards judge. Open to strategic advisory, and speaking opportunities — reach out on LinkedIn.

Experience

Uber

Software Engineer

Oct 2018 – Jan 2020 · 1 yr 3 mos · Palo Alto, California, United States

Built real-time analytics systems.
Improved streaming pipeline efficiency.
Designed OLAP workflows at scale.
Reduced latency for analytics teams.
Improved reliability of critical data paths.
Realtime Analytics, Stream Processing. Kafka, Flink, AresDB, Pinot, Presto. Data Platform. Pipelines Manager.

Realtime AnalyticsStream ProcessingKafkaFlinkAresDBPinot+3

Consulting (self)

Engineering Consultant and Advisor

Jan 2018 – Present · 8 yrs 2 mos · San Francisco Bay Area

Guided startups through AI platform choices.
Designed scalable ML architectures.
Enabled faster product iteration cycles.
Advised founders on technical strategy.
Supported teams building Generative AI products.

Google

AI/ML Platform Architect

Jan 2016 – Present · 10 yrs 2 mos · Mountain View, California, United States

Built AI platforms for vision workloads.
Improved reliability of ML systems.
Delivered high-scale xM qps inference.
Designed large-scale distributed systems.
Led core infra initiatives across teams.
Enabled faster ML experimentation cycles.
Artificial Intelligence, Computer Vision, Data infrastructure, Distributed Systems

Artificial IntelligenceComputer VisionData infrastructureDistributed Systems