- Technical Lead with a multidisciplinary skill set spanning Data Science, NLP, and Distributed Systems Engineering.
- Several years of industry experience in leading large and complex projects in Machine Learning and Distributed Systems.
- Graduate and Professional degrees in Computer Science and Artificial Intelligence.
- A pragmatic who is passionate about technology, learning new things, and helping others to work better and more effectively.
Microservices, Scalable and Highly-Available Distributed Systems, Machine Learning, Natural Language Processing, Functional and Object-Oriented Programming.
2018—Present: Principal Engineer, Machine Learning at Workday
Technical Lead of the Machine Learning Platform team; built container-based systems that address all aspects of the ML workflow:
- Train, version, and deploy ML models created using a variety of toolkits and programming languages.
- Expose models as services with REST endpoints for easy integration into business applications.
- Manage the complete lifecycle of the deployed ML apps with zero downtime, including updating runtime artifacts, scaling, monitoring, and security.
Currently working on Document Understanding using Computer Vision (OCR) and NLP to extract, categorize, and validate data from business documents to automate enterprise workflows.
2011—2017: Software Engineer, Siri at Apple
Led the design and development of several ML-based systems that power the virtual personal assistant.
- Implemented new domains, ontologies, and request processing pipelines to expand Siri’s skill set.
- Improved the NLP system by introducing statistical techniques in parsing and query understanding.
- Launched Siri on new platforms: macOS, Apple tv, and HomePod.
2008—2011: Software Engineer, Kindle at Amazon
Responsible for the design and implementation of Web services, tools, and utilities to support Amazon's growing business in digital content, including music, movies, and the wireless reading device, Kindle. The systems processed hundreds of millions of transactions daily, pushing the limits of traditional data management and posing unique challenges in scalability and fault-tolerance.
- Designed the Digital Vendor Services workflow, enhancing scalability, reducing latency, and separating operational and reporting aspects of the system.
- Built the Identity and Content Delivery systems for the Kindle E-reader.
2003—2008: Software Engineer, SQL Server at Microsoft
Contributed to the design and implementation of two Object-Relational Mapping technologies, LINQ to SQL as well as the Entity Framework, that shipped as part of the .NET runtime in SQL Server 2008.
1995—2003: Software Engineer, AutoCAD at Autodesk
Made significant and noteworthy contributions to six releases of the flagship product.
- Designed and implemented APIs to allow third-parties to extend the AutoCAD platform.
- Led the development of client-side Internet functionality, as well as support for Digital Signatures and Encryption across the product line.
- Graduate Certificate in Artificial Intelligence, Stanford University, 2014.
- M.Sc. in Computer Science, University of California, Riverside.
- Java, Scala, Python, SQL, C++
- Scalable and Highly-Available Distributed systems, Amazon Web Services (AWS)
- Machine Learning, Deep Learning with Neural Networks, PyTorch / Keras / TensorFlow
- Natural Language Processing (NLP), Natural Language Understanding (NLU)
Available upon request. Some endorsements can be found on my LinkedIn page.