# Sanjeev Suresh > Software Engineer at YouTube Location: San Francisco Bay Area, United States Profile: https://flows.cv/sanjeevsuresh ## Work Experience ### Software Engineer - Youtube Living Room Discovery @ YouTube Jan 2021 – Jan 2023 ### Senior Software Engineer @ Harvested Financial Jan 2020 – Jan 2021 Took a professional risk joining a small seed-stage startup as engineer #3. Harvested Financial was the first robo-advisor to manage financial derivatives for retail investors. Built core infrastructure, engineering processes, and data security practices. - designed and implemented a security strategy for encryption of all customer PII including SSN, address, tax filings, DOB, etc using client-side field level encryption - developed re-usable event-driven architectures using GCP Cloud Scheduler, GCP Pub / Sub, and Compute Engine for ETLs that batch process customer data - developed core CI / CD pipelines using GCP Cloud Build / Bitbucket and latest python testing frameworks (tox, pipenv, pytest, etc) I learned a lot about financial derivatives, options markets, early-stage startup business needs, and building financial applications. ### Software Engineer, Machine Learning @ 23andMe Jan 2017 – Jan 2020 Developed the machine learning platform at 23andMe, which uses ML to provide predictions to customers on their risk for genetically-linked diseases. Built tools to speed up the iteration cycle for engineers and data scientists and solutions for the end-to-end ML lifecycle: training, deploying, bulk computing, serving, monitoring, and model management. - developed automated pipelines and datastores that monitor the performance of models in production and display statistical metrics in both custom web applications and Databricks MLFlow - scaled services for training & serving models on large genomic datasets using Elastic Container Service (ECS) and AWS Batch - built a real-time prediction service with 200ms latency for model serving while increasing the infrastructure limit for both larger and more accurate models by 10x I learned how to build and architect machine learning applications in AWS and tools for data scientists ### Machine Learning Engineer @ Socos LLC Jan 2016 – Jan 2017 | San Francisco Bay Area I worked for the data science team at Socos, a startup that combines behavioral psychology and machine learning to make recommendations for parenting and child development. - modeled the latent factors for neighborhoods (zipcode specific) using public information for IRS tax returns and demographic data - developed the personalized recommender system for survey style questions that users receive everyday - clustered similar user profiles, imputed answers to questions users haven’t answered, and leveraged the semantic relatedness of questions - created visualizations for user engagement and profiles on personality attributes of children I learned how to take ML into production and what’s state-of-the-art through reading papers and great mentorship. ### Software Engineering Intern for Tokenization Services @ Visa Jan 2015 – Jan 2015 | Foster City I worked for Visa Token Services – the API for Apple Pay and Google Wallet. I prototyped a dashboard for my manager to compile # of open bugs, release stages, health of different environments, etc., across teams in one place. Using a MEAN stack, I mostly developed the front-end views & charts using Angular, but I also contributed to the Mongo ‘schema’ (although Mongo is schema-less) and created new APIs for additional features. I learned a lot about security in the payments industry. ### Software Engineering Intern @ Cloudian Inc Jan 2014 – Jan 2014 | Foster City Cloudian is S3-compatible object storage for enterprise cloud. I compared the in-house solution to the open-source framework Openstack Swift by using open-source benchmarking software, but also writing some of my own tests in Java using their existing codebase & drivers. I learned about architectural choices for object-storage such as the uses of NoSQL databases like Cassandra & Redis, and concepts like master/slave, rings, and replication. ## Education ### EECS in Electrical Engineering & Computer Science University of California, Berkeley ## Contact & Social - LinkedIn: https://linkedin.com/in/sanjeev-suresh --- Source: https://flows.cv/sanjeevsuresh JSON Resume: https://flows.cv/sanjeevsuresh/resume.json Last updated: 2026-03-29