Alex Peter
📧 alex.peter@email.com 📱 (555) 123-4567 📍 San Francisco, CA 🔗 linkedin.com/in/alex-peter 🐙 gith
ub.com/alexpeter
ub.com/alexpeterSummary
Senior Software Engineer with 8+ years of experience building scalable, distributed systems and AI-powered applications at high-growth tech companies. Proven expertise in backend development (Java, Python, Go), cloud infrastructure (AWS, GCP), and machine learning deployment. Delivered systems handling 10M+ daily users with 99.99% uptime. Passionate about engineering excellence, technical mentorship, and solving complex scalability challenges.
Technical Skills
Java Python Go TypeScript React Node.js TensorFlow PyTorch Kubernetes Docker AWS GCP Kafka gRPC CI/CD
Professional Experience
Senior Software Engineer
Google (YouTube)
- Designed and implemented a real-time recommendation ranking service using TensorFlow Serving and Kubernetes, improving CTR by 12% and reducing latency by 35%.
- Architected a sharded microservice for user activity logging handling 500K RPM; migrated from monolith to event-driven architecture using Kafka and gRPC.
- Led a team of 5 engineers to build a scalable A/B testing framework adopted by 20+ product teams, increasing experiment velocity by 40%.
- Optimized CI/CD pipelines with Bazel and internal tooling, reducing build time from 15min to 4min and deployment failures by 60%.
Software Engineer
Meta (Facebook)
- Developed backend services for Facebook Groups’ notification system in Java and Thrift, serving 2B+ users with sub-100ms p99 latency.
- Integrated ML models for spam detection (PyTorch) into production pipelines, reducing false positives by 22% and manual review load by 30%.
- Contributed to internal Kubernetes operator for stateful services, improving deployment reliability and reducing on-call incidents by 45%.
- Mentored 3 junior engineers; conducted code reviews and design doc feedback for cross-team initiatives.
Software Developer
Netflix
- Built and maintained backend services for personalized content discovery using Spring Boot and Cassandra; handled 10M+ daily requests.
- Designed a fault-tolerant caching layer with Redis and Hazelcast, reducing database load by 70% and improving API response time by 50%.
- Implemented observability with Prometheus, Grafana, and ELK stack; reduced mean time to detect (MTTD) incidents by 65%.
- Participated in SRE rotation; improved service SLA from 99.9% to 99.99% over 18 months.
Education
Master of Science in Computer Science
Stanford University
Focus: Distributed Systems & Machine Learning | GPA: 3.9/4.0
Bachelor of Engineering in Computer Science
University of California, Berkeley
Graduated Summa Cum Laude | Dean’s List all semesters
Certifications & Achievements
- AWS Certified Solutions Architect – Professional (2023)
- Google Cloud Professional Data Engineer (2022)
- Published paper: “Scalable Real-time Recommendation at YouTube Scale” at ACM RecSys 2022
- HackerRank: Top 0.5% globally (Algorithm & Data Structures)
Master Web Development in 2026
A practical, project-based guide to modern JavaScript, React, and full-stack development. Includes 50 real-world exercises and downloadable code.
- 500+ pages of step-by-step tutorials
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