Ashish Rastogi

Director of Engineering

Los Angeles, California, United States18 yrs 6 mos experience

Most Likely To SwitchHighly Stable

Key Highlights

Expert in machine learning and AI foundations.
Led innovative projects at Netflix for content personalization.
Strong background in quantitative finance and algorithms.

Stackforce AI infers this person is a Machine Learning and AI expert in the B2C entertainment industry.

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Skills

Core Skills

Machine LearningAlgorithmsData MiningQuantitative Finance

Other Skills

PythonDistributed SystemsMultimodal content understandingGenerative modelsData AnalysisComputer ScienceProgrammingAnalysisTime Series AnalysisOptimizationHadoopMapReduceApache Spark

Experience

18 yrs 6 mos

Total Experience

3 yrs 8 mos

Average Tenure

9 yrs 6 mos

Current Experience

Netflix

5 roles

Director

Sep 2025 – Present · 7 mos

Leading the AI Foundations team at Netflix, responsible for building core foundation models that power personalization, recommendations, and search. We’re pioneering the Netflix member LLM to deeply understand our members, our content, and to deliver trusted, high-quality generative AI experiences at scale to our members.

AlgorithmsMachine LearningData MiningPythonDistributed Systems

Director, AI/ML, Content & Media ML Foundations

Promoted

Dec 2023 – Sep 2025 · 1 yr 9 mos

I lead the Content & Media ML Foundations team at Netflix. Our charter is to transform Netflix’s unique content and media data into a strategic advantage through foundational machine learning.
Our team focuses on multimodal content understanding—developing semantic representations of frames, shots, scenes, and titles across video, audio, text, and images. These serve as building blocks for downstream models and decision-making across Netflix’s core business areas, including content, studio, personalization and ads.
We also invest in long-horizon R&D to explore the future of generative media technologies. This includes training generative models from scratch to better understand the strategic value of Netflix’s data, build differentiated in-house capabilities, and enhance content production and promotion through GenAI-powered tools.

Machine LearningData MiningPythonMultimodal content understandingGenerative models

Director, Content Intelligence & Demand Modeling

Promoted

Dec 2020 – Dec 2023 · 3 yrs

My team supports content decisions with model driven insights at scale. We innovate on ML models that predict our members’ demand for titles and their foundational components (e.g. IP, story elements etc).

Machine LearningData MiningPython

Manager, Content Demand Modeling

Sep 2018 – Dec 2020 · 2 yrs 3 mos

Led a team of scientists & engineers responsible for a suite of machine learning models supporting content valuation and informing content strategy.

Machine LearningData MiningPython

Senior Machine Learning Scientist, Content Demand Modeling

Sep 2016 – Aug 2018 · 1 yr 11 mos

Led the design and development of a suite of machine learning models responsible for forecasting the audience of shows prior to launch.

Machine LearningData MiningPython

Bloomberg lp

Senior Software Engineer - Machine Learning, Search and Discoverability

Oct 2014 – Sep 2016 · 1 yr 11 mos · Greater New York City Area

Worked in the Search & Discoverability group on various strategic projects in collaboration with the CTO's office. Responsibilities included:
Design and development of a framework for improving the relevance of content presented on the Bloomberg Terminal through the application of machine learning methods.
Collaborate with academic researchers on various large-scale machine learning problems to advance the state-of-the-art and apply those ideas to Bloomberg products.

Machine LearningData MiningPython

Goldman sachs

Quantitative Strategist

Oct 2009 – Sep 2014 · 4 yrs 11 mos · New York City

Quantitative Desk Strategist in the Alternative Investments and Manager Selection (AIMS) group within the Investment Management Division of Goldman Sachs.
Responsibilities included:
Design and development of robust quantitative tools for risk-management and portfolio-construction.
Conducting research and publishing articles on the hedge fund industry, including analyses of returns over time, sources of alpha, and performance persistence.
Building quantitative models to systematically implement trading strategies.

Quantitative FinanceAlgorithmsData Analysis

Google

2 roles

Research Engineer

Jul 2008 – Sep 2009 · 1 yr 2 mos · Greater New York City Area

Developed and designed a new pricing guidance algorithm (patent filed) for alternative Ad markets that improves market efficiency and leads to a X% more accurate prediction of the closing price of an Ad post negotiation between a buyer and seller.
Designed an elaborate web-page classification framework for confidential internal search quality projects.

AlgorithmsMachine Learning

Research Intern

May 2007 – Jul 2007 · 2 mos · Greater New York City Area

Novel Ranking Algorithms & Search Quality
Developed theoretical methods for understanding the quality of several transductive regression algorithms. (summer 2007)
Designed, implemented and analyzed the performance of novel ranking algorithms. (summer 2006)
 Designed and implemented machine learning based algorithms for improved quality estimation. (summer 2005)

Trilogy

Developer

May 2003 – May 2004 · 1 yr · Bangalore, India

Worked on the development of an innovative high business value pricing optimization application for a Fortune 500 client. Awarded a biannual Trilogy award in recognition.

Eurecom

Research Intern

May 2002 – Jul 2002 · 2 mos

Quality of Service Support in Mobile Network Routing Protocols: Worked on the design and implementation of a routing protocol with Quality of Service support.

Max planck institute for informatics

Research Intern

May 2001 – Jul 2001 · 2 mos · Saarbrücken Area, Germany

Efficient Disc-scheduling Algorithms: Compared existing disc-scheduling algorithms in terms of latency and time complexity. Proposed a new disc-scheduling algorithm that outperformed existing algorithms.