Delon Saks
Verified Expert in Engineering
AI Developer
Austin, TX, United States
Toptal member since March 6, 2025
Delon is an AI leader with a proven track record in driving innovation in generative AI and machine learning. He has led high-impact projects across energy, heavy asset industries, eCommerce, and sports. Working with major enterprises such as General Electric and the LA Dodgers, as well as innovative startups such as Cognite and Tachyus, Delon develops AI solutions that enhance decision-making, leveraging AI multi-agent systems, RAG pipelines, and deep learning to deliver business value.
Portfolio
Experience
- Python 3 - 8 years
- FastAPI - 4 years
- Claude - 2 years
- LangChain - 2 years
- AI Chatbots - 2 years
- Retrieval-augmented Generation (RAG) - 2 years
- AI Agents - 2 years
- LlamaIndex - 2 years
Preferred Environment
MacOS, Python 3
The most amazing...
...project I've worked on was consulting with a national oil company in the UAE to develop subsurface reservoir models for effective CO2 sequestration.
Work Experience
Senior AI Engineer/Advisor
Hearst - Technology
- Built enterprise AI systems at Hearst across legal knowledge management, real-time voice agents, and ambient meeting intelligence, translating complex workflows into production-grade applications for business users.
- Developed secure RAG and agentic AI applications using OpenAI, Anthropic, Gemini, Microsoft Graph, SharePoint, Qdrant, Twilio, Azure, FastAPI, WebSockets, MCP, Docker, and Terraform.
- Created executive-facing AI tools that help teams search private knowledge, capture structured insights from conversations, automate support intake, and evaluate voice-agent quality with measurable rigor.
Lead AI Engineer Consultant
Los Angeles Dodgers
- Led the initiative with senior business executives and technical experts to ideate, develop, and deploy the enterprise's first GenAI MVPs, currently used and tested by senior scouts and technical and business personnel.
- Built an agentic RAG system that enables scouts to interact with player data. Fine-tuned bi-encoder and cross-encoder models on domain-specific data.
- Developed and deployed an advanced AI scouting agent that enables advanced insights from structured numerical data.
AI Engineer
Metagame Content LTDA
- Developed an agentic RAG app that allows poker professionals to easily source answers from a curated list of documentation from various sources.
- Built an AI agent prototype that interacted with a structured database containing detailed poker-solver data and provided accurate odds per hand to poker professionals.
- Developed the front end for the back-end Python application using React and deployed using Docker.
Senior AI Engineer
Cognite
- Recruited as the 1st data scientist in Cognite's inaugural US office just two months after its founding. Developed innovative solutions for enterprise clients leveraging contextualized data sources, including time series, text, and images.
- Directed data science efforts on the largest project in the US office, working alongside an agile team co-located with a super-major energy company. Managed the project from use case development to successful renewal after 18 months.
- Co-developed an unsupervised machine learning workflow that identifies analogous subsurface designs by integrating global data from six distinct source systems, streamlining the subsurface planning process for a super-major energy company.
- Developed a deep learning workflow utilizing an LSTM autoencoder to identify anomalies in subsurface survey designs using real-time sensor data to reduce non-productive time.
ML Engineer
Tachyus
- Led the optimization process with Tachyus’ three largest enterprise customers through machine learning-assisted reservoir modeling.
- Presented technical development work to senior business stakeholders at large, international client enterprises.
- Co-authored a fourth technical paper, which was published at a recognized industry association.
Senior Subsurface Simulation Engineer
General Electric
- Developed and optimized physics-based reservoir models using subsurface data to support super-major energy companies and national oil corporations.
- Directed the full-field modeling development plan for an independent energy company in China, achieving a reduction of over 15% in water usage across their field.
- Co-authored four published technical papers on subsurface physics-based reservoir modeling.
Experience
MLB Scouting Assistant
Education
Master's Degree in Data Science
University of California, Berkeley - Berkeley, CA, USA
Certifications
CFA Level 2
CFA
Skills
Libraries/APIs
OpenAI API, React, PyTorch, Scikit-learn, TensorFlow, PySpark
Tools
Claude, DeepSeek
Languages
Python 3, Python, R
Frameworks
LlamaIndex
Platforms
Docker, MacOS, Databricks, Azure, Amazon Web Services (AWS), SharePoint
Other
Qdrant, Amazon Bedrock AgentCore, AI Agents, AI Chatbots, Retrieval-augmented Generation (RAG), OpenAI, Anthropic, Natural Language Processing (NLP), Time Series, Data, FastAPI, Large Language Models (LLMs), Artificial Intelligence (AI), Meta Llama, Agentic AI, Time Series Forecasting, Generative Artificial Intelligence (GenAI), LangChain, Hugging Face, Data Science, Statistics, Machine Learning, Modeling, Physics, Computer Vision, Finance, Fine-tuning, Data Engineering
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