Ritendra Datta

CTO

San Francisco, California, United States16 yrs 3 mos experience

Highly StableAI Enabled

Key Highlights

Led AI teams at top tech companies.
Expert in machine learning and algorithm design.
PhD in applied machine learning.

Stackforce AI infers this person is a Machine Learning Leader with expertise in SaaS and social media technologies.

Contact

ritendra.datta@gmail.com LinkedIn

Skills

Core Skills

Artificial IntelligenceMachine LearningApplied AiEngineering ManagementSoftware EngineeringTeam Leadership

Other Skills

AI developmentAI team scalingAI/BI optimizationAI/MLAlgorithm DevelopmentAlgorithm designApplied AI team buildingAutomatic Code CompletionCode reviewsCodingData AnalyticsDatabricks AssistantLLM-powered Interviewing AgentsML algorithm developmentML and Infra engineering

About

I've started external mentoring: https://mentorcruise.com/mentor/ritendradatta/ ** Please DON'T SEND CONNECTION REQUESTS unless we know each other -- I have over 10K pending connection requests, with no time or help to manage them. I've stopped reviewing them. ** Everything I write is my personal view. They never represent the views of my past or present employers, nor reviewed or vetted prior to posting. I am not even authorized to speak on their behalf. I sometimes write notes under the blog named TLDR0: https://tldr0.substack.com/ ** The real 'About me' ** Machine learning leader with AI and ML-related academic and work experience at Google, Facebook, Databricks, IBM Research, Xerox PARC, and Penn State. Managed teams ranging from 2 to 215 engineers and research scientists. Worked on ML, Infra, and algorithms for search, recommender systems, computer vision, data analytics, etc. Completed PhD in applied ML in ~4.5 years right after Bachelors (via 'direct' PhD admission). Started coding at age 8 with GW-BASIC, moved to C/Assembly. In grad school I switched from Theoretical CS to Statistical Modeling and AI/ML, because I love probability and statistics.

Experience

Eightfold

VP of AI

Feb 2025 – Present · 1 yr 1 mo · Santa Clara, California, United States

Scaling up the AI team responsible for Profile-to-Role Matching, Resume parsing, LLM-powered Interviewing Agents, Post-interview candidate scoring, and so on. The AI Interviewing agent is the harder AI/ML problem I've ever had to work on in my career - it's a very interesting problem space.

AI team scalingProfile-to-Role MatchingResume parsingLLM-powered Interviewing AgentsPost-interview candidate scoringArtificial Intelligence+1

Databricks

Senior Director of Engineering & Head of Applied AI

Aug 2023 – Feb 2025 · 1 yr 6 mos · Mountain View, California, United States

Built out the Applied AI team, responsible for all AI work that makes the Databricks product smarter, faster, better, more efficient. The team's responsible for the ML/LLMs powering the Databricks Assistant, Search Ranking, Automatic Code Completion for Notebooks/SQL, Automatic Data Documentation, Text2SQL, AI/BI (Genie spaces), optimization for scalable Serverless, etc. Helped build and launch automatic code completion, AI/BI, improved search, improved assistant, optimized resource allocation, and so on.

Applied AI team buildingML/LLMsDatabricks AssistantSearch RankingAutomatic Code CompletionText2SQL+3

Facebook

Director of Engineering / Head of FB Reels and Video Recommendations

Jul 2019 – Aug 2023 · 4 yrs 1 mo · Menlo Park, California, United States

When I left Facebook, I was leading a ~200 person team of ML and Infra engineers and scientists responsible for Reels and video recommendations. In this ~1.5 year time, Reels on Facebook grew massively, largely due to the ranking work my team did. Team size peaked at ~214.
Previously, I led engineers, scientists, and managers responsible for Ranking/Recs/Search of Video, Audio, and Gaming, Facebook Watch and autoplaying Videos on Newsfeed. Grew team from ~30 to ~120, took on Reels recommendations charter. Video consumption grew over 5X during this time.

ML and Infra engineeringVideo recommendationsRanking algorithmsTeam leadershipMachine LearningEngineering Management

Google

Senior Staff Software Engineer / Tech Lead / Manager / Summer Intern

May 2010 – Jul 2019 · 9 yrs 2 mos · Mountain View, CA

Google was my first full-time job. When I left, I was managing a team of 30 engineers working on shopping-related searches. Founded and managed multiple teams related to shopping searches on Google (structured query understanding, ML based task understanding, personalization, etc.). Deeply enjoyed staying technical writing code, algo design, code reviews, etc. Also contributed via reviewing launches, doing interviews, hiring committees, promotion committees, on-campus visits, talks, etc.
Briefly worked on the Google self-driving car's (now Waymo) simulation software.

Shopping-related searchesTeam managementAlgorithm designCode reviewsSoftware EngineeringTeam Leadership

Xerox parc

Summer Intern

Jun 2007 – Aug 2007 · 2 mos · Palo Alto, CA

Developed an ML algorithm (rooted in Tree-augmented Naive Bayes) for improved de novo sequencing of proteins. Made a non-proprietary version of the TAN Bayes code publicly available.

ML algorithm developmentProtein sequencing

Ibm tj watson research center

Summer Intern

May 2006 – Sep 2006 · 4 mos · Yorktown Heights, NY

Developed a new algorithm for multivariate sequence clustering, to aid resource demand forecasting. Improved the complexity of Viterbi-like sequence decoding for hidden semi-Markov models.

Multivariate sequence clusteringResource demand forecasting