Tomas Fernandez

Seasoned AI/ML Engineer with 7 years of hands-on experience building production-grade models across speech, vision, LLMs, and agentic systems. I have led large-scale AI initiatives at Chevron and Snap, delivering real-time Voice AI, high-accuracy computer-vision pipelines, and enterprise LLM applications used by thousands of users. I fine-tune speech-native models, optimize TTS systems with ONNX/TensorRT/Triton, and design reliable pipelines for both cloud and edge. I am strong in multi-agent architecture, RAG systems, AIOps, and high-throughput ML services. I mentor engineering teams, drive technical strategy, and build AI systems that improve accuracy, reduce latency, and scale smoothly in real environments.

Data Scientist — Chevron (2018–2020)

Senior Machine Learning Engineer — Chevron (2020–2022)

Lead Machine Learning Engineer — Chevron (2022–2025)

Machine Learning Engineer — Snap (2025)

Bachelor of Science in Petroleum Engineering — The University of Tulsa (2013–2017)

Master of Science in Business Analytics — The University of Texas at Austin, McCombs School of Business (2017–2018)