Tomas Romo
@tomasromo
Senior AI/ML Engineer with 10+ years of experience in machine learning.
What I'm looking for
I am a Senior AI/ML Engineer with over 10 years of experience in designing and deploying machine learning systems across fintech and enterprise environments. My expertise lies in fraud detection, risk modeling, and NLP-driven automation, utilizing technologies such as Python, PyTorch, and XGBoost. I have a proven track record of building real-time ML pipelines and scalable infrastructure on cloud platforms like AWS and GCP.
Throughout my career, I have successfully led cross-functional initiatives and mentored engineers, delivering AI solutions that align with strategic business goals. My work includes integrating large language models into generative AI applications and developing frameworks for federated learning, ensuring compliance with regulations such as FCRA and GDPR. I am passionate about sharing knowledge and have conducted numerous training sessions on MLOps best practices and responsible AI principles.
Experience
Work history, roles, and key accomplishments
Senior AI/ML Engineer
Accenture
Jan 2023 - Present (2 years 6 months)
Led end-to-end AI/ML initiatives for clients focusing on fraud detection, risk modeling, and customer personalization, delivering scalable and compliant solutions. Architected real-time ML pipelines utilizing AWS services including S3, SageMaker, Lambda, and Kinesis, ensuring high availability and low-latency processing.
AI/ML Engineer
Stripe
Dec 2021 - Jan 2023 (1 year 1 month)
Developed state-of-the-art NLP models to automate dispute classification and extract customer interaction insights, improving resolution times and accuracy. Implemented deep learning architectures with PyTorch, including attention-based models, to enhance fraud prediction capabilities on complex transaction data.
Machine Learning Engineer
Stripe
Jun 2017 - Dec 2021 (4 years 6 months)
Led the architecture and development of real-time fraud detection systems using gradient boosting frameworks such as XGBoost and LightGBM, achieving high precision and recall in live environments. Designed and deployed scalable ML infrastructure leveraging GCP, Kubernetes, Apache Airflow, and Docker, supporting rapid iteration and continuous deployment.
Data Scientist
Square
Oct 2015 - Jun 2017 (1 year 8 months)
Built and validated advanced machine learning models for fraud detection and risk assessment, leveraging Python, scikit-learn, and Spark to improve accuracy and scalability. Designed and implemented predictive scoring systems for merchant credit risk and transaction anomaly detection, increasing early risk identification rates.
Education
Degrees, certifications, and relevant coursework
University of Texas - Austin
Bachelor of Science, Computer Science
2011 - 2015
Studied Computer Science at the University of Texas - Austin. Gained foundational knowledge and practical skills in various aspects of computer science.
Tech stack
Software and tools used professionally
Availability
Location
Authorized to work in
Job categories
Skills
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