I bring my experience and passion as a Machine Learning engineer and advisor to companies that need help defining their AI strategy, building or growing ML teams, improving their ML pipelines and scale ML systems on the cloud. Projects include:- computer vision for patient observation at https://www.ouva.co/products/care-automation- recommender system for walmart- reinforcement learning and genAI for a gaming studioI do some private tutoring on the side to share my passion for computer science in general and AI in particular

First batch of full time engineers. Built several aspects of the infrastructure including monitoring and automated provisioning of edge devices. Redesigned and implemented critical parts of the core codebase to increase the productivity of scientists and enable more complex ML pipelines in production

work across teams in the AI dept and sometimes lead collaborations with other departments. Led strategic decisions to focus both ML and unity developers on building tools to generate synthetic data for computer vision using unity. I helped narrow the scope of the domains and tasks of an initial release of the open source perception package. I also defined the scope and some design of the public python package which was also open sourced to support the consumption of the synthetic data generated by the perception package. I co-authored three blogposts and several public talks on the use of synthetic data generated with unity.helped identify the need and led discussions for 1yr on a new internal simulation platform that would support workloads such as distributed RL and automated domain randomization. This led to the creation of a simulation platform team.established and hosted weekly AI lightning talks, reading groups for computer vision, python and software design, and monthly AMA sessions to promote transparency and alignment in the AI dept.Co-authored a proposal to fund a new company-wide ML platform team. I'm one of two tech leads defining the components and prioritizing the work being done for this cross company ML platform and making design decisions along the ways as we onboard teams onto it. Using tools like kubeflow, katib and mlflow.

Joined as the first engineer in the AI dept with broad goals of making unity better using ML.Helped define unity ML agents and contributed to the project until it's first public releaseIdentified the opportunity and led the development of ML services all the way to production for the unity asset store. Work includes the first personalized recommendations and visual similarities

* Automating Hyperparameter Optimization for recommendation models.* Using Neural Nets to produce personalized recommendations across categories and devices. https://github.com/amznlabs/amazon-dsstne* AWS Amazon Machine Learning service launch team https://console.aws.amazon.com/machinelearning/*Same-Day delivery launch team. http://www.amazon.com/sameday*China global store launch team. *Automate the process of determining export eligibility using Machine Learning.

Write backend software for a large-scale automated classification and review service using tools like Hadoop and Pig on AWS Elastic Map Reduce (EMR)

Led and prepared weekly discussion sessions for the School of Engineering focused on Engineering ethics and technical writing.

Designed and developed a minimal DHCP server to net boot production devices in data centers as part of an automated installation process.

· Designed and developed a novel algorithm to work with satellite images and its web interface. Used temperature and chlorophyll concentration information extracted from these images to compute the area of different upwelling systems · Implemented web applications to view metadata extracted from satellite images with temperature, chlorophyll and wind information using Python, JavaScript and MySQL with the TurboGears framework to integrate other tools that were previously developed at the Institute. · Developed a completely automated process that downloads, transforms and inserts the satellite images into the databases for later use by the web applications, including the creation of bash scripts to manipulate the SeaDAS software during extraction of the data. · Redesigned the website of the Digital Observatory project that hosts the software developed at the institution.

· Migrated a running MySQL and Apache server across different linux distributions (Gentoo & Arch).

· Mantained a small network with 7 windows clients, 2 printers, 1 linux server. Installed and configured various network services including: Apache, Subversion, Bind, Postfix