🧙‍♂️ Ryan Russon Email & Phone Number

Eagle Mountain, Ut, Us

Mclean, Va, Us

Leading teams responsible for developing and sustaining enterprise tools and cutting-edge platforms. These platforms empower large-scale, compute-intensive model training, enhance customer experiences, and enable generative AI capabilities for millions of Capital One customers.

Chicago, Illinois, Us

Chicago, Illinois, Us

I assist large companies solve their toughest data challenges while teaching them best practices in the cloud. I provide our clients with the knowledge and tools to leverage the ever-improving services within the major cloud vendor offerings.MLOps leader, managing efforts for uncovering the best practices in ML and data systems for varying team sizes, business situations, and problem types. Leads the implementation of new training and serving solutions for global clients utilizing Kubeflow on AWS and GCP. Includes custom SDKs, CI/CD, and testing procedures for both model delivery and production pipelines.Led the implementation and design of a fuzzy matching model and supporting platform architecture for record deduplication at scale on AWS. Utilized various AWS services such as Glue, Lambda, DyanamoDB, RDS, SNS, SQS to resolve matches against billions of records, reducing execution time by 96%.Built an end-to-end model training platform for traceability and repeatability on terabytes of data for a delivery forecasting system on GCP, using Kubeflow Pipelines to orchestrate Vertex AI, BigQuery, and GCS with Stackdriver logging. Reduced model training time by 80% and improved model predictionperformance by 4%-10% over the client model.Delivered POC for topic modeling solution that leveraged Streamlit, AWS Transcribe, SageMaker, and S3 to derive major topics for call-center conversations to inform leadership on recurring and high-profile help desk services rendered.

Boise, Idaho, Us

Developed deep learning, traditional computer vision, and other predictive models for anomaly detection and automated reactions to manufacturing issues. Worked with cross-functional teams to provide custom classification and object recognition deep learning models using Python from data provided by end-users through an in-house, custom web interface that allows for quick image classification before model building. Models classify difficult manufacturing issues and are deployed in intervention systems, saving the company thousands of dollars per week in sourcing and preventing quality issues.Built active learning solutions that automatically apply human-classified data to previously trained deep learning models for continuous improvement of detection systems and model accuracy.Combined various relational data sources (MSSQL, Oracle, etc.) and NoSQL sources (Spark + Hadoop) to provide bespoke data sources for new insights and analytics from manufacturing systems.Designed and owned data pipelines utilizing PySpark, Hadoop (HBase), and Snowflake for distributed compute of scheduled and demanding workloads.Collaborated with data analysis team in structuring data for feature engineering in sourcing fab-critical manufacturing issues removing human bias and allowing for root cause identification.Created custom models utilizing REST APIs for easy scaling and on-demand data analytics, predictions, and classifications.Designed web interfaces to deliver real value to in-house engineering customers for predictive solutions and data mining.Explores the creation of ML pipelines using cloud software for robust and scalable solution.

Lehi, Ut, Us

Owned several Python and PySpark ETL jobs transferring data from various Micron and Intel world-wide SQL and NoSQL data sources (Oracle, MSS, MySQL, HBase) to local sources with data aggregates which improved fab engineer data accessibility and cleansing tasks by over 300%.Created custom microservices in PHP/Python allowing easy-to-access data solutions and quick prototyping of new analytical insights.Built a custom web interface using PHP/Python/JavaScript that allows users to create and submit landmark image data on wafers to Apache HBase that is later used in conjunction with a bespoke search algorithm to source wafer defects saving 60 engineering hours per month.Created a custom web service in Django that solves constrained optimization for automatic process control models reducing human error by 98% and saving over +$1M per year in human-caused product excursions. Won award for the company’s best data and ops solution.

Lehi, Ut, Us

Engineering lead over the development and improvement of automatic process control software used to enhance process capability and maintain the highest level of quality for innovative memory and storage products in diffusion and wet process. Worldwide leader for dynamic wafer sampling strategies used to augment current metrology sampling capabilities and tasked with Micron network alignment.Developed methodology to derive R2R process control models in diffusion from inline data saving hundreds of hours of tool time and thousands of dollars in resources over traditional DOEs methodsLed a team of engineers and technicians on 1.5-year project to standardize and improve R2R training, business processes and policies with the end goal to amplify knowledge, communication and visibility for higher quality standards Managed a cross-area project between metrology and RDA that implemented sampling schemes and software modifications to save 60 engineering hours per month and reduce Special Work Request setup by 30%

Washington, Dc, Us

Selected as the primary advisor for the Commanding Officer to the main regulatory organization and prime contractor for the Navy’s Nuclear Power School (NPS). Managed the command’s internal audit and continuous improvement program comprised of more than 60 individual programs, 30 divisions, and 4,000 personnel. Provided oversight for all technical curricula and administrative procedures and develop training programs and policy.Standardized critical training program maintaining technical requirements while lowering the man-hours invested by 50%Managed the implementation of an enterprise-scale LCMS projected to improve management of technical content by 75% Directed the Commanding Officer’s project team consisting of diverse departments tasked with implementing a superior software replacement for the current program used for process improvement and tracking, reducing the IT department load by 20% Reshaped current infrastructure for certifying examinations to use secure electronic practices which raised communication and turn-around time from months to days for critical changes between the prime contractor and NPS

Washington, Dc, Us

Program manager for Navy Equal Opportunity and Sexual Harassment program, leading a team of seven personnel in the resolution of over 50 workplace climate conflicts command-wide and issuing large-scale annual climate assessment. Improved program efficiency by 95% by structuring specific duties among subordinate team membersContributed 800 additional hours directing a team of 30 personnel in the Navy's annual command climate assessments resulting in improved program enhancements and increased personnel morale

Washington, Dc, Us

Selected among peers to instruct advanced course on theory and design of the complex electrical and mechanical support systems for nuclear power plant operation for more than 300 personnel with a 97% course completion rate. Consistently ranked as ‘Excellent’ on staff and student evaluations. Recognized as resident expert in electrical control system design with outstanding instructional ability, providing the foundation on which designation as a Master Training Specialist (MTS) was earned Organized and implemented a training program that dramatically improved staff operational training in a power plant environment

Salt Lake City, Utah, Us

Worked as a research assistant at the University’s premier imaging institute developing a model in order to predict the onset of Alzheimer’s disease (AD) by studying a precursor condition known as mild cognitive impairment. Created UNIX and Python-scripted, imaging workflows for processing hundreds of MRI scans Applied statistical methods (i.e. partial least squares, bootstrapping and ANOVA) to predict onset of AD

Salt Lake City, Utah, Us

Executed critical functions and developed manufacturing equipment and processes for full-scale production of a new medical device. Led tests during verification and validation phases of a new medical device Experience in rapid prototyping, design history file maintenance and manufacturing operating procedures

Master Of Science (M.S.), Electrical And Computer Engineering

Bachelor Of Science (B.S.), Biomedical Engineering