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Etimbuk Esau

@etimbukesau1

Message

Staff machine learning engineer architecting distributed GenAI systems with enterprise-grade reliability.

United States

Message

What I'm looking for

I’m looking to build and scale production GenAI and distributed ML platforms—RAG, streaming pipelines, and Kubernetes inference—working with cross-functional, cross-regional teams to deliver enterprise-grade throughput and reliability.

I’m a Staff Machine Learning Engineer with 8+ years architecting distributed AI/ML systems and streaming pipelines that process multiple terabytes of data per hour. I focus on productionizing GenAI frameworks, scaling advanced RAG systems, and optimizing distributed inference.

I’ve delivered measurable impact in throughput and reliability—architecting distributed inference endpoints on AWS EKS with Triton Inference Server and dynamic batching to achieve a 2.8x increase in model throughput, while maintaining 99.99% service availability for enterprise-grade applications.

In recent roles, I’ve built production GenAI platforms: a distributed multi-agent LLM system using open-source models to automate identity governance workflows, and a high-performance RAG pipeline with hybrid semantic search, context reranking, and optimized vector chunking across 50M+ unstructured records.

I also lead end-to-end MLOps and scalable data/streaming architectures—establishing CI/CD validation, drift detection, MLflow tracking, and real-time UEBA detection pipelines. I enjoy partnering across teams to define technical roadmaps and ship high-performance AI infrastructure that keeps pace with ambitious delivery goals.

Experience

Work history, roles, and key accomplishments

Current

Staff Machine Learning Engineer

Current

SailPoint

Sep 2025 - Present (10 months)

Architected and productionized a distributed multi-agent GenAI platform using open-source LLMs to automate identity governance workflows, reducing access review processing time by 42%. Optimized distributed inference on AWS EKS with Triton Inference Server and dynamic batching to increase model throughput 2.8x while reducing infrastructure overhead by 35%.

Identity Governance RAG Triton Inference Server Distributed Inference

Software Engineer

Stealth Startup

Aug 2024 - Jun 2025 (10 months)

Developed and productionized a self-improving LLM orchestration layer using RLAIF and agentic loops to automate complex B2B workflow generation, achieving a 95.2% end-to-end task success rate. Built scalable ingestion and MLOps automation for multimodal data processing and fine-tuning infrastructure.

RLAIF Orchestration Reinforcement Learning Python fastAPI Qdrant PyTorch DeepSpeed Hugging Face Accelerate Multi GPU Training MLFlow CI CD

Lead Software Engineer

Sumo Logic

Jun 2021 - Aug 2024 (3 years 2 months)

Architected and delivered UEBA machine learning detection engines for a real-time rules framework powering the Cloud SIEM product, detecting zero-day threats 40% faster. Migrated a mission-critical Kafka Streams pipeline from AWS EC2 to Kubernetes (EKS) microservices with zero downtime and improved engineering velocity by 65%.

UEBA Détection Kafka Kafka Streams Microservices Kubernetes Real Time Rules Framework Machine Learning Pipelines Stateful Behavioral Anomalies RESTful APIs gRPC

Data Scientist

ExoAnalytic Solutions

May 2019 - May 2021 (2 years)

Designed and implemented a robust containerized CI/CD automation pipeline for a geographically distributed sensor network, reducing deployment cycles from 4 days to under 45 minutes using Docker. Built radar data generation and distributed processing workflows to accelerate deep learning model training and improve inference performance on edge nodes.

Docker CI CD Automation Deep Learning PyTorch NumPy Distributed Data Processing Edge Inference Optimization Low Latency Systems

Education

Degrees, certifications, and relevant coursework

The University of Alabama in Huntsville

Bachelor of Science (B.S.), Aerospace Engineering

Completed a B.S. in Aerospace Engineering, focusing on computational modeling, numerical methods, fluid dynamics, and system telemetry.

Concordia College

Bachelor of Arts (B.A.), Mathematics and Computer Science

Completed a B.A. in Mathematics and Computer Science, focusing on data structures and algorithms, linear algebra, advanced calculus, and software engineering foundations.