Kapil Anand

Engineering Manager

San Francisco, California, United States18 yrs 6 mos experience

Most Likely To SwitchAI ML Practitioner

Key Highlights

15+ years in software architecture and machine learning.
PhD with 15+ publications and patents.
Co-founded a successful cybersecurity startup.

Stackforce AI infers this person is a Cybersecurity and Machine Learning expert with extensive experience in software architecture.

Contact

kapilanand@google.com LinkedIn

Skills

Core Skills

Machine LearningDistributed SystemsCyber-securityEntrepreneurshipCompilersSoftware Engineering

Other Skills

AlgorithmsApplication Performance ManagementBinary AnalysisBinary Machine Code AnalysisBinary RewritingBinary Rewriting FrameworkBinary TranslationCC++Computer ArchitectureComputer ScienceDynamic Binary TranslationEmbedded SystemsEnterprise SoftwareGenAI

About

Experienced engineering leader with 15+ years of industrial experience in software architectural design, machine learning, large-scale distributed systems and 8+ years of management experience. Deep subject matter expert in distributed systems, machine learning, AI, cloud infrastructure and enterprise security. PhD and Research experience with 15+ publications/patents in compilers and processor architecture-specific optimizations. Entrepreneurial experience with co-founding a startup in enterprise security and performance monitoring.

Experience

Google

Engineering Manager & Tech Lead

Dec 2017 – Present · 8 yrs 3 mos

Owning and driving a critical domain of reducing abuse using Machine Learning and GenAI
Owned and scaled scanning large-scale pipelines to meet requirements for 1B+ Gmail consumers and 30M+ enterprise Gmail customers.
Led and developed a RAG based review assistant agent to enable faster, more efficient and accurate review of policy violations for different abuses. Achieved 4X increased efficiency in reviews and enforcements of policy violations.
Drove projects for using GenAI to identify phishing, malware and social engineering threats and generate threat insights in enterprise security products. 3X increase in detection of threats using GenAI methods.

Machine LearningGenAILarge-scale PipelinesPolicy Violations ReviewThreat DetectionDistributed Systems

Secondwrite llc

Co-founder and CTO

Aug 2013 – Nov 2017 · 4 yrs 3 mos · College Park, MD

SecondWrite is developing next-generation cyber-security solution for handling sophisticated evasive malware specifically designed to defeat existing cybsecurity protections. The solution is based on deep research innovations in binary machine code analysis.
SecondWrite is based in the incubator of University of Maryland, College Park. It was founded by UMD researchers who have rich research experience in program analysis and security.
SecondWrite is a Phase II, NSF SBIR funded company. SecondWrite was selected among the top three startups among 30 applicant companies at the TechStars Startup DC competition in 2016.

Cyber-securityBinary Machine Code AnalysisStartup DevelopmentResearch InnovationsEntrepreneurship

Intel corporation

Graduate Intern

Jun 2010 – Aug 2010 · 2 mos · Santa Clara, CA

Analyzed workloads for performance improvement in a dynamic binary translation system.

Dynamic Binary TranslationPerformance ImprovementSoftware Engineering

University of maryland

Graduate Student

Aug 2007 – Jul 2013 · 5 yrs 11 mos · College Park, MD

Worked broadly in the field of analysis of binary/machine code(desktop applications). Specific research projects include
SecondWrite : A new binary rewriting framework based on a compiler high level Intermediate representation (LLVM). SecondWrite can be used for analyzing and rewriting desktop applications with least amount of restrictions, and in the most general manner. Novel aspects of the system include use of a compiler intermediate format and updating commerical off-the shelf applications.
Symbolic analysis framework for executables: Implemented a symbolic analysis framework, which extends the traditional source level analysis like based value numbering to binary code. This framework also results in a practical system which can implement multiple information-flow security policies.
Memory Management inside Binary Rewriter : Worked on a broad research area of improving onchip memory performance by optimally utilizing software controlled memories such as scratch-pad and lockable caches.

Binary Rewriting FrameworkSymbolic AnalysisMemory ManagementCompilersSoftware Engineering