Mobile Developer with React Native & TypeScript Expertise
Resume:
Daval Cato
Irvine, CA *****
818-***-**** • *********@*****.***
LinkedIn: https://www.linkedin.com/in/daval-c-27288112/ GitHub: https://github.com/davalcato
LeetCode: https://leetcode.com/u/DavalC/
PRINCIPAL ARCHITECT CLOUD AI & ENTERPRISE
ARCHITECTURE
Enterprise cloud architect and AI engineering leader with 10+ years of experience designing scalable cloud- native platforms, multimodal AI systems, and enterprise-grade infrastructure across distributed environments. Proven expertise advising technical leadership teams, architecting high-performance AI workloads, and driving modernization initiatives using Kubernetes, AWS EKS, edge inference, and large- scale distributed systems.
Experienced collaborating with executive stakeholders, engineering organizations, and cross-functional product teams to align technical architecture with business outcomes. Strong background in cloud strategy, AI platform optimization, real-time systems, DevOps, and enterprise integration architecture. Core strengths include cloud infrastructure modernization, AI/ML platform architecture, enterprise systems integration, Kubernetes orchestration, edge computing, and scalable multimodal AI solutions. TECHNICAL EXPERTISE
Cloud & Enterprise Architecture
Enterprise Architecture Strategy
Cloud-Native Infrastructure Design
Distributed Systems Architecture
Hybrid & Edge Computing Architectures
Technical Solution Design
Executive Technical Advisory
Cross-Functional Technical Leadership
Enterprise Integration Strategies
High-Availability & Fault-Tolerant Systems
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Cloud Platforms & Infrastructure
Kubernetes
AWS EKS
Docker
CI/CD Pipelines
Infrastructure Automation
Cloud Deployment Strategies
Observability & Monitoring
Scalability Optimization
Performance Engineering
AI / Machine Learning
Large Language Models (LLMs)
Multimodal AI Systems
Real-Time Inference Pipelines
LLaMA-2
CLIP
Whisper
LoRA / QLoRA
Quantization & Distillation
Edge AI Deployment
Drift Detection Systems
Human-in-the-Loop Training Pipelines
Programming & Frameworks
Python
Swift
C++
PyTorch
CoreML
CUDA
LLaMA.cpp
REST APIs
Distributed AI Workloads
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PROFESSIONAL EXPERIENCE
EyeAeon – Remote
Chief Technology Officer (CTO) Jul 2023 – Present Lead enterprise-scale AI architecture initiatives focused on multimodal assistants, edge inference systems, and cloud-native AI infrastructure for spatial computing applications. Enterprise Cloud & AI Architecture
Architected scalable AI infrastructure leveraging Kubernetes and AWS EKS for distributed multimodal inference workloads.
Designed cloud-native deployment pipelines enabling rapid delivery and lifecycle management of AI services across distributed environments.
Collaborated with engineering stakeholders to define scalable platform strategies for latency- sensitive AI applications.
Built enterprise-ready infrastructure patterns focused on resiliency, observability, uptime, and operational scalability.
AI Platform Engineering & Optimization
Quantized and optimized LLaMA-2-7B inference workloads using q4_0 techniques, reducing latency by 40% while maintaining production-grade performance. Integrated Whisper and LLaMA pipelines to power real-time voice-driven assistant experiences for immersive computing environments.
Developed C++ accelerated drift detection systems achieving 99.8% uptime reliability across long- running AI workloads.
Designed lightweight multimodal inference systems using CLIP and on-device AI architectures for mobile and AR applications.
MLOps & Cross-Functional Leadership
Implemented containerized MLOps pipelines supporting rapid model deployment, telemetry collection, and continuous optimization workflows. Established feedback-loop systems enabling automated fine-tuning and human-in-the-loop model improvements.
Worked across engineering, product, and infrastructure teams to align technical roadmaps with platform scalability goals.
Presented technical architecture strategies and AI infrastructure concepts to internal stakeholders and collaborators.
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Me2 Software – Los Angeles, CA
Senior AI Research Engineer May 2014 – Jul 2023
Led the design and implementation of scalable AI infrastructure and multimodal systems powering high- volume consumer applications and intelligent device ecosystems. Scalable AI & Distributed Systems
Architected a CLIP-based semantic search platform supporting over 2M+ daily API calls across multimodal environments.
Designed distributed inference workflows integrating speech, gaze, and scene-context processing for real-time AI responsiveness.
Improved infrastructure efficiency through model quantization and distillation strategies, reducing operational costs by 70% while maintaining intent accuracy. Contributed to enterprise-grade AI platform scalability, observability, and deployment optimization efforts.
Cloud Engineering & Platform Optimization
Supported cloud-native deployment initiatives and infrastructure modernization for AI-driven applications.
Collaborated with technical teams to optimize AI workloads for scalable deployment across mobile, cloud, and edge environments.
Contributed to performance tuning initiatives for latency-critical AI systems. Assisted in defining architecture best practices for multimodal AI integration. Research, Open Source & Technical Leadership
Released a PyTorch quantization toolkit adopted by AR/VR developers and startups. Contributed to lightweight model packaging initiatives for mobile and wearable AI deployment. Shared technical expertise through open-source contributions and AI optimization research. Mentored developers and contributed to technical direction across AI platform initiatives. AcTV8me – Los Angeles, CA
iOS Engineer (AI Focus) Jan 2014 – Apr 2014
Developed mobile AI capabilities and optimized on-device inference systems for consumer-facing applications.
Converted PyTorch vision models to CoreML for sub-200ms on-device object detection. Built Swift wrappers around LLaMA.cpp to enable offline conversational AI experiences. Contributed to early AR-enhanced product recognition initiatives for mobile applications. Assisted with AI model integration and mobile performance optimization.
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LEADERSHIP & ARCHITECTURE HIGHLIGHTS
Trusted technical leader experienced aligning business goals with scalable AI and cloud infrastructure strategies.
Strong ability to communicate complex technical architecture concepts to engineering leadership and executive stakeholders.
Experienced collaborating across infrastructure, product, AI research, and engineering organizations.
Deep understanding of enterprise-scale system reliability, deployment optimization, and distributed infrastructure.
Proven ability to evaluate technical tradeoffs and design scalable cloud-native solutions. Passionate about emerging AI infrastructure, multimodal systems, and enterprise cloud transformation.
RESEARCH & OPEN SOURCE
Whitepaper: Efficient LLM Fine-Tuning for Edge Devices (2023) Research: Bias Mitigation in Foundation Models for AR Assistants (In Progress) Open-source contributions focused on:
LLaMA.cpp optimizations
Drift detection libraries
CLIP wrapper utilities
AI inference optimization tooling
EDUCATION
University of Southern California (USC)
Master of Science (M.S.), Computer Science – Artificial Intelligence & Machine Learning Bachelor of Science (B.S.), Computer Science
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