Tech Lead · Meta · Former Technical Lead Manager & SDM · Amazon
AI/ML Engineer & Researcher · 10+ Years
Engineering leader specializing in AI, Machine Learning, and large-scale data infrastructure.
Rajesh Vakkalagadda is a Tech Lead at Meta and a recognized expert in Machine Learning, Causal Inference, and large-scale data engineering. With over 10 years of specialized experience at the intersection of applied AI research and production-scale engineering, he has built systems that power decisions worth billions of dollars at two of the world's most influential technology companies.
At Meta, Rajesh leads a team of software engineers building the ads calibration platform, directly impacting at least 85% of Meta's revenue-generating ad-streams. He is also pioneering AI-agent-based automation to onboard teams at 5× scale, working across Ads, WhatsApp, and AI product lines.
Before Meta, Rajesh spent nearly eight years at Amazon, rising from Software Development Engineer to Technical Lead Manager and Software Development Manager. He was one of the founding team members of the Downstream Impact (DSI) causal inference program, helping build the ML models that informed Amazon's strategic decisions across Alexa, Whole Foods, and its multi-billion-dollar marketing portfolio. He was also an early member of the EV&O product team. As SDM, he led the Forge platform for ML experimentation, which was adopted company-wide. He co-authored a publication on Double Machine Learning at Scale, available on Amazon Science.
Rajesh is a prolific technical author with 30,000+ article views across HackerNoon and DZone. He has been an invited judge at the Society of Women Engineers national awards program (published in SWE Magazine), the Globee® Awards for Innovation, Meta's internal Creator Competition series, and eight collegiate hackathons across the United States. He has also been invited by senior executives at ETV Win and AHA Media to conduct expert technical and security peer reviews of their platforms.
He holds a Master of Science in Computer Science from Arizona State University and a Bachelor of Engineering from IIIT Hyderabad. He is a Fellow of the British Computer Society (FBCS) and an IEEE Senior Member, two of the highest professional grades in international computing and engineering.
Over 10 years of progressive engineering and leadership roles at two of the world's most influential technology companies.
| Period | Role | Company | Focus |
|---|---|---|---|
| Jan 2025 – Present | Tech Lead |
Meta | Ads calibration platform impacting 85%+ of Meta's ad revenue; AI-agent-based automation across Ads, WhatsApp, and AI product lines |
| Dec 2023 – Jan 2025 | Software Development Manager |
Amazon | Led the GCCP Foundations team; oversaw Causal Inference and MLOps workstreams including the Forge ML experimentation platform |
| Dec 2022 – Dec 2023 | Technical Lead Manager |
Amazon | Scaled Downstream Impact (DSI) causal inference program; ML models informing multi-billion-dollar strategic decisions across Alexa and Whole Foods |
| May 2019 – Dec 2022 | Software Development Engineer II |
Amazon | Built core ML and data engineering systems; large-scale distributed data pipelines using Apache Spark; early team member of the EV&O product |
| Jun 2017 – Apr 2019 | Software Development Engineer I |
Amazon | Foundational engineering role; distributed systems and large-scale data infrastructure; early contributor to the DSI causal inference program |
| 2014 – 2016 | MS, Computer Science |
Arizona State University | Graduate studies in distributed systems, algorithms, and cloud computing; Graduate Services Assistant for CSE 531: Distributed Operating Systems |
Formal recognition from elite global professional bodies, international award programs, and the world's most competitive technology companies.
| Honor | Issuing Body | Details |
|---|---|---|
Fellow of the British Computer Society (FBCS) |
BCS, The Chartered Institute for IT | Highest grade of BCS membership; fewer than 4% of 70,000+ global members hold Fellow status |
IEEE Senior Member (SMIEEE) |
Institute of Electrical and Electronics Engineers · Seattle Section | Highest IEEE grade attainable by application; fewer than 10% of 400,000+ members worldwide |
Stevie Award: Thought Leadership |
The Stevie Awards (SASCS) · International Business Award Program | Recognized for published technical contributions and influence in the ML/AI engineering community · View Winners → |
Senior Engineering Leader at Meta & Amazon |
Meta · Amazon · 2017–Present | 9+ years of sustained upward progression at two of the world's most selective technology employers |
CodePath Technical Coach, 6+ Years |
CodePath Non-profit · Volunteer · April 2020–Present | Mentored students from underrepresented backgrounds for 6+ years; nationally recognized non-profit |
Peer-reviewed research and widely-read technical articles. For live citation count and h-index, visit the Google Scholar profile below.
| Title & Authors | Venue | Link |
|---|---|---|
|
Double Machine Learning at Scale to Predict Causal Impact of Customer Actions
Rajesh Vakkalagadda · Applied/Research Scientists · Economists · Amazon
|
Amazon Science (Publicly Indexed) |
Read Paper → |
| Title | Platform | Views | Link |
|---|---|---|---|
The 3 Stages of MLOps |
HackerNoon | 6,200+ views |
Read → |
A Practical Guide to Scalable Job Scheduling for Cloud and Big Data |
HackerNoon | 6,000+ views |
Read → |
Smart Sampling at Scale Using Spark and the Central Limit Theorem |
HackerNoon | 5,600+ views |
Read → |
Using Browser Network Calls for Data Processing |
HackerNoon | 5,500+ views |
Read → |
Browser Network Calls for Data Processing |
DZone | 5,000+ views |
Read → |
Inside a Large Retailer's Web Architecture |
DZone | 1600+ views |
Read → |
Efficient Sampling Approach for Large Datasets |
DZone | 1200+ views |
Read → |
Rajesh's work at Amazon has been covered by leading business and technology publications, and he is an active published author on major technical platforms.
| Publication | Title | Link |
|---|---|---|
Wall Street Journal |
Why Amazon Isn't Making Money Off Alexa | View → |
Wall Street Journal |
Amazon Alexa and Echo: Losses & Strategy | View → |
The New York Times |
Amazon Buys Whole Foods for $13.4 Billion | View → |
TechSponential |
Amazon Devices: Industry Analysis | View → |
Amazon Science |
Double Machine Learning at Scale (Research Publication) | View → |
HackerNoon 4 Articles · 23,000+ Views |
Author Profile: MLOps, distributed systems, big data engineering | View → |
DZone 3 Articles · 8,500+ Views |
Author Profile: scalable data architecture and browser-based data engineering | View → |
SWE Magazine Society of Women Engineers |
Listed as FY25 Awards Program Judge | View → |
Formally selected to evaluate peers and students across professional awards programs, internal competitions at Meta, and collegiate hackathons spanning the United States.
Served as Judge for the following professional awards programs and industry competitions.
| Event | Organization | Scope |
|---|---|---|
SWE Engaged Ally Award National Award Program · Published in SWE Magazine |
Society of Women Engineers (SWE) | Evaluated nominees from Boeing, Cummins, John Deere, and Whirlpool; officially listed as judge in SWE Magazine |
Globee® Awards for Innovation International Business Awards Program |
Globee Awards · GlobeeAwards.com | Industry Judge evaluating innovation across technology companies worldwide |
Meta Creator Competition Mobile Innovation & Open Source World Series |
Meta Horizon Worlds · MHCP Competition Team | Judged two competitions in Meta's Always On Creator Competition Series; evaluations noted for quality and depth |
Invited as an expert reviewer by industry organizations to assess security, code quality, and infrastructure.
| Organization | Type | Scope |
|---|---|---|
ETV Win etv.co.in · Indian OTT Streaming Platform |
Security & Code Review | Identified three vulnerabilities: API security issue, geofencing bypass, unauthenticated streaming flaw |
AHA Media arhamedia.com · Media Technology Company |
Security & Infrastructure Review | Reviewed public-facing code and network interactions; submitted multiple infrastructure reports |
Served as Judge for the following collegiate hackathons across the United States.
| Event | Institution / Host | Location |
|---|---|---|
RevolutionUC |
ACM @ University of Cincinnati | Cincinnati, OH |
FullyHacks |
California State University, Fullerton | Fullerton, CA |
DiamondHacks |
ACM @ UC San Diego | San Diego, CA |
RocketHacks |
University of Toledo | Toledo, OH |
tidalTAMU HACK |
Texas A&M University | College Station, TX |
SkillsUSA Washington State |
SkillsUSA Washington | Olympia, WA |
HackDavis |
University of California, Davis | Davis, CA |
United Hacks V5 |
HackUnited | Online |