- Backend software engineer in Software Engineering (SWE) org - Owned web service which processed 100 logs/second coming off device 24x7 - Owned Jenkins batch job service processing 1000 batch jobs per day - Led our transition from on-prem to cloud based Kubernetes deployments - Built CICD pipelines to support cloud migration, automated unit testing and linting - Created an integration test suite for the web service. Created a culture of test driven development (TDD) and code reviews. Created a playbook for the team and our sibling SRE team to handle production incidents - Refactored web service code base to support batched API calls thus reducing cross data center networking and speeding up log processing by 20% - Built and migrated new backend API across 3 webservices to speed up log processing by 10% and transitioned 93% of calls to old endpoint to new endpoint. - Split apart our monolith into 5 separate services and migrated 2 of them from Python2 to Python3 - Tech stack - Python, Flask APIs, SQL, Kubernetes, Docker, Docker, Grafana, Hubble, Splunk, Jenkins, Object Store

Backend Software Engineer in Software Infrastructure Org. - Build and maintain tooling and backend services in Python that support Quantitative traders (Quants). - Primarily writing code in Python and SQL. - Tech stack: Python, Flask APIs, SQL, managed Kubernetes, Git, Docker, Grafana, Parquet, Arrow, Object Store

- Developed and operationalized the world’s first cloud-native Wildfire Spread Model using Python, Docker, AWS Batch, and Lambda - Led the successful launch of Jupiter’s operational wildfire risk product (FireScore Ops) - Led Product Management, Science, Technical Project Management (Jira and Confluence), and Business Development on a team of up to 15 in a matrix-based organization at an early stage startup

- Systems architecture, construction, and operationalization of a cloud-based weather decision support system using Numerical Weather Prediction (NWP) models on HPC supercomputers - ETL pipelines running every 5 minutes 24x365 in Python, Bash, and Postgres with data churn of ~200Gb/day - Achieved 14 weeks of zero maintenance operations through fault tolerant reliability engineering - Created web based dashboard visualization using Javascript, HTML, CSS - Invention and commercialization of Intellectual Property through licensing agreement with Univ of Nevada

- Created and batch processed 30 Tb downscaled climatology using NWP WRF model for wildfire risk analysis for allowing allowing prioritization of wildfire mitigation efforts and reporting to CPUC - Training and operationalization of logistic regression model in Python using Scikit-learn to forecast wildfire risks - Architected, constructed, and operationalized state of the art realtime NWP model for forecasting wildfire danger and utility power shut-off events - Developed and taught Python Programming for Atmospheric and Hydrologic Science applications, UNR Graduate School (2018, 2016, 2014). Mentored many graduate students - Funding: $2.1M as Primary Investigator (2013-2020) from sponsors: NSF, DOD, DOE, Google, Moore Foundation - Service: Amer. Met. Soc. Wildfire, Technology and Risk Committee (2019-2022), and Renewable Energy Committee (2015-2018), UNR Atmospheric Science Graduate Admission Committee (2013-2018) - Popular media: LA Times, Bloomberg News, Daily Beast, NPR Across the Nation, KTVN, Discovery Channel - Publications and Citations link: https://scholar.google.com/citations?user=INKTFyYAAAAJ

- Backend software engineer in Software Engineering (SWE) org - Owned web service which processed 100 logs/second coming off device 24x7 - Owned Jenkins batch job service processing 1000 batch jobs per day - Led our transition from on-prem to cloud based Kubernetes deployments - Built CICD pipelines to support cloud migration, automated unit testing and linting - Created an integration test suite for the web service. Created a culture of test driven development (TDD) and code reviews. Created a playbook for the team and our sibling SRE team to handle production incidents - Refactored web service code base to support batched API calls thus reducing cross data center networking and speeding up log processing by 20% - Built and migrated new backend API across 3 webservices to speed up log processing by 10% and transitioned 93% of calls to old endpoint to new endpoint. - Split apart our monolith into 5 separate services and migrated 2 of them from Python2 to Python3 - Tech stack - Python, Flask APIs, SQL, Kubernetes, Docker, Docker, Grafana, Hubble, Splunk, Jenkins, Object Store

Backend Software Engineer in Software Infrastructure Org. - Build and maintain tooling and backend services in Python that support Quantitative traders (Quants). - Primarily writing code in Python and SQL. - Tech stack: Python, Flask APIs, SQL, managed Kubernetes, Git, Docker, Grafana, Parquet, Arrow, Object Store

- Developed and operationalized the world’s first cloud-native Wildfire Spread Model using Python, Docker, AWS Batch, and Lambda - Led the successful launch of Jupiter’s operational wildfire risk product (FireScore Ops) - Led Product Management, Science, Technical Project Management (Jira and Confluence), and Business Development on a team of up to 15 in a matrix-based organization at an early stage startup

- Systems architecture, construction, and operationalization of a cloud-based weather decision support system using Numerical Weather Prediction (NWP) models on HPC supercomputers - ETL pipelines running every 5 minutes 24x365 in Python, Bash, and Postgres with data churn of ~200Gb/day - Achieved 14 weeks of zero maintenance operations through fault tolerant reliability engineering - Created web based dashboard visualization using Javascript, HTML, CSS - Invention and commercialization of Intellectual Property through licensing agreement with Univ of Nevada

- Created and batch processed 30 Tb downscaled climatology using NWP WRF model for wildfire risk analysis for allowing allowing prioritization of wildfire mitigation efforts and reporting to CPUC - Training and operationalization of logistic regression model in Python using Scikit-learn to forecast wildfire risks - Architected, constructed, and operationalized state of the art realtime NWP model for forecasting wildfire danger and utility power shut-off events - Developed and taught Python Programming for Atmospheric and Hydrologic Science applications, UNR Graduate School (2018, 2016, 2014). Mentored many graduate students - Funding: $2.1M as Primary Investigator (2013-2020) from sponsors: NSF, DOD, DOE, Google, Moore Foundation - Service: Amer. Met. Soc. Wildfire, Technology and Risk Committee (2019-2022), and Renewable Energy Committee (2015-2018), UNR Atmospheric Science Graduate Admission Committee (2013-2018) - Popular media: LA Times, Bloomberg News, Daily Beast, NPR Across the Nation, KTVN, Discovery Channel - Publications and Citations link: https://scholar.google.com/citations?user=INKTFyYAAAAJ