Cesar Salcedo is a founding engineer with nine years of experience building production-ready ML systems and developer tools that prioritize user-centered interactions. He blends machine learning research—spanning reinforcement learning, multi-agent control, and transformer-based models—with hands-on product engineering, from training PyTorch models to deploying containerized services and CI/CD on AWS. At startups and research labs he has shipped features like a trip-status classifier, a natural-language object query engine for WhatsApp agents, and standardized messaging schemas to unlock downstream ML pipelines. His background includes accelerating experiments and infra (multi-GPU orchestration and reproducible pipelines) and automating large-scale web data collection using modern LLM stacks. Based in Lima with visiting stints at Berkeley and UNM, he pairs academic rigor with pragmatic system design to move prototypes into production. An underappreciated strength is his knack for turning research code into maintainable engineering—yielding measurable speedups and clearer data pipelines for product teams.
9 years of coding experience
5 years of employment as a software developer
Visiting Student Program, Computer Science, Visiting Student Program, Computer Science at University of California, Berkeley
Visiting Student Program, Computer Science, Visiting Student Program, Computer Science at The University of New Mexico
Bachelor's degree, Computer Science, Bachelor's degree, Computer Science at UTEC - Universidad de Ingeniería y Tecnología
Contributions:2 PRs, 108 pushes, 1 branch in 1 year 3 months
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