Senior AI Engineer, ML Platforms

Ryan Berti

Senior AI Engineer

****.*.*******@*****.*** +1-415-***-**** Los Angeles, CA 90027

PROFESSIONAL SUMMARY

Senior Artificial Intelligence Engineer with over 14 years of experience designing scalable machine learning platforms, AI models, and data-driven solutions across leading technology and media organizations. Expertise includes Python, TensorFlow, PyTorch, Keras, NLP, computer vision, cloud AI platforms, and statistical modeling. Proven success delivering production AI systems through cross-functional collaboration, model optimization, and reliable deployment strategies. TECHNICAL SKILLS

Artificial Intelligence: Machine Learning, Deep Learning, Artificial Intelligence, Natural Language Processing, Computer Vision, Statistical Modeling, Machine Learning Algorithms, Predictive Modeling

Frameworks: TensorFlow, PyTorch, Keras, Scikit-learn, Apache Spark, Hadoop Programming: Python, Java, SQL, Scala, R, Data Structures Cloud Platforms: AWS SageMaker, Google Cloud AI Platform, Amazon Web Services, Google Cloud Platform, Cloud Computing, Distributed Systems

Engineering: Model Deployment, Model Optimization, MLOps, Data Engineering, API Development, System Design, Software Development, Agile Methodology WORK EXPERIENCE

Netflix Los Angeles Metropolitan Area

Lead AI Engineer Jan 2021 - Present

• Netflix entertainment platforms benefited from advanced AI engineering initiatives focused on machine learning models, Python development, TensorFlow workflows, and scalable systems supporting personalized content discovery.

• Designed and deployed deep learning models for Netflix recommendation ecosystems using Keras architectures, statistical modeling techniques, and optimized pipelines improving reliability across global streaming operations.

• Developed natural language processing solutions for Netflix content intelligence by applying machine learning algorithms, Python automation, and large-scale data processing frameworks.

• Implemented computer vision models for Netflix media analysis workflows using deep learning techniques, TensorFlow frameworks, and performance optimization strategies across distributed environments.

• Collaborated with Netflix product and engineering teams to integrate AI models into existing systems through scalable APIs, cloud infrastructure, and robust deployment methodologies.

• Optimized machine learning models at Netflix by improving inference performance, resource utilization, and scalability through advanced algorithms, model tuning, and production monitoring practices.

• Built AI engineering solutions for Netflix streaming experiences using Python, PyTorch, Keras, and statistical approaches supporting data-driven business growth and customer engagement.

• Applied MLOps practices within Netflix AI environments to automate model lifecycle management, deployment pipelines, validation processes, and operational reliability improvements.

• Created predictive analytics solutions for Netflix business intelligence initiatives by combining machine learning algorithms, large datasets, and scalable cloud-based processing architectures.

• Enhanced Netflix AI capabilities through research and implementation of emerging artificial intelligence technologies including NLP models, computer vision systems, and deep learning methods.

• Led technical growth initiatives at Netflix by mentoring engineering teams on AI frameworks, model development practices, and production-grade machine learning implementation strategies.

• Delivered enterprise AI solutions for Netflix media platforms by integrating advanced modeling techniques, cloud services, and reliable machine learning architectures supporting global users. Quibi Los Angeles, CA

AI Engineer Nov 2019 - Nov 2020

• Quibi mobile entertainment platforms leveraged AI engineering expertise through machine learning model development, Python applications, and scalable solutions supporting personalized video experiences.

• Developed artificial intelligence models for Quibi content systems using TensorFlow, Keras, and statistical modeling techniques designed for efficient media recommendation capabilities.

• Integrated NLP solutions within Quibi workflows by creating machine learning pipelines that processed content information and improved automated understanding across digital platforms.

• Built computer vision applications for Quibi video services using deep learning frameworks, image analysis methods, and optimized model architectures for reliable performance.

• Collaborated across Quibi engineering teams to deploy AI models into existing systems using cloud technologies, API integrations, and scalable software development practices.

• Improved Quibi AI infrastructure through model optimization, performance testing, and machine learning lifecycle enhancements supporting emerging streaming industry requirements. The Walt Disney Company Glendale

Machine Learning Engineer Aug 2019 - Nov 2019

• The Walt Disney Company media operations advanced through machine learning engineering contributions involving AI models, Python development, and analytics solutions for entertainment platforms.

• Designed predictive models for The Walt Disney Company using statistical techniques, machine learning algorithms, and scalable data workflows supporting business intelligence initiatives.

• Developed NLP and data processing capabilities for The Walt Disney Company content ecosystems through AI frameworks, automation tools, and advanced modeling methodologies.

• Supported The Walt Disney Company digital transformation efforts by implementing reliable AI solutions, optimizing model performance, and collaborating with cross-functional technology teams. OpenX Pasadena, CA

Machine Learning Engineer May 2016 - Aug 2019

• OpenX advertising technology platforms utilized machine learning engineering expertise to create AI models, Python services, and scalable data solutions improving digital advertising intelligence.

• Developed predictive machine learning models for OpenX ad technology systems using statistical modeling, feature engineering, and advanced algorithms supporting marketplace optimization.

• Built distributed AI pipelines at OpenX using Python, Apache Spark, and cloud computing approaches to process large datasets and enhance advertising decision systems.

• Implemented NLP techniques for OpenX advertising workflows by creating intelligent classification models, automated analysis solutions, and scalable machine learning applications.

• Optimized OpenX machine learning systems through performance tuning, model validation, and deployment improvements supporting reliable advertising platform operations.

• Collaborated with OpenX engineering and product teams to integrate AI capabilities into existing platforms using APIs, software development practices, and automated workflows.

• Applied deep learning approaches within OpenX environments to improve predictive analytics, recommendation capabilities, and data-driven advertising technology outcomes.

• Advanced OpenX AI engineering initiatives through research, experimentation, and implementation of emerging machine learning technologies across digital advertising solutions. Teradata San Diego, CA

Software Engineer May 2012 - May 2016

• Teradata enterprise data solutions gained advanced software engineering capabilities through development of scalable systems, analytics platforms, and data processing applications.

• Built data-driven applications at Teradata using Java, Python, SQL, and distributed computing concepts supporting enterprise analytics and large-scale information management.

• Developed machine learning foundations for Teradata analytics products by applying statistical methods, data engineering practices, and algorithmic optimization techniques.

• Enhanced Teradata database and analytics environments through software improvements, automation frameworks, and performance optimization strategies for enterprise customers.

• Implemented scalable data processing solutions at Teradata using Hadoop, Apache Spark, and distributed architectures supporting complex business intelligence workloads.

• Collaborated with Teradata engineering teams to design reliable software components, improve system efficiency, and deliver technology solutions for enterprise data industries.

• Supported Teradata product evolution through technical development, quality improvements, and integration of advanced data management capabilities across analytical platforms.

• Established foundational engineering expertise at Teradata by developing enterprise software systems, database solutions, and scalable architectures enabling future AI advancements. EDUCATION

University of Southern California 2012

M.S. Computer Science

University of Southern California 2010

B.S. Computer Science

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