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Adriel Acosta

@adrielacosta

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Senior AI and Data Engineer specializing in ML, GenAI, and production deployments.

United States

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What I'm looking for

I seek senior roles building production ML/AI systems where I can lead technical design, mentor teams, and deliver secure, scalable ML products in healthcare or enterprise domains.

I bring extensive experience in applying machine learning (ML), including Generative AI (GenAI), across diverse fields and complex challenges. I have worked on ML applications in ad security, supply chain management, business analytics, image tracking, healthcare technology, and failure prediction. I have successfully led teams and managed projects from initial conception through full deployment in both startup and enterprise environments.

Experience

Work history, roles, and key accomplishments

Senior AI & Data Engineer

iOPEX Technologies

May 2020 - May 2025 (5 years)

Developed and deployed containerized services using Docker to deliver these features and standalone interfaces for rapid iteration. Provided a roadmap to develop AI features from concept to MVP, including architecture, integration, infrastructure, LLM model selection, feedback, training, and cost/quality trade-offs.· Trained 3 engineers to progress from beginners to production-level proficiency.

Docker Python TensorFlow PyTorch LLMs MLOps Data Analysis MATLAB Mathematica)Predictive Analysis Machine Learning LLM Containerization NLP

Senior Data Engineer

EPAM Systems

May 2017 - Oct 2019 (2 years 5 months)

Built real-time object detection and ECG classification models, developed a 3D convolutional autoencoder for heart mapping, and implemented dataset annotation systems and secure data controls across distributed databases.

Computer Vision Deep Learning 3D Conv Autoencoder REST APIs Data Annotation Encryption Python Convolutional Networks Convolutional Neural Networks (CNN)Object Detection RSA ECC6

Machine Learning Engineer

GE Healthcare

Jul 2013 - Mar 2017 (3 years 8 months)

Developed the Tube Watch predictive monitoring system, designed multimodal failure-prediction algorithms for CT machines, and built NLP classifiers and optimized preprocessing to process ~100M records in 2 hours on a single machine.

NLP Time Series Data Engineering Python Signal Processing Optimization Machine Learning Classification Healthcare Healthcare Technology Healthcare Operations

Education

Degrees, certifications, and relevant coursework

Loyola University Chicago

Bachelor of Science, Computer Science

2009 - 2013

Grade: 3.7

Activities and societies: AI club

Completed a Bachelor of Science in Computer Science, covering core computer science principles and practical software development from August 2009 to May 2013.