# Steve Thomas > Senior Software Engineer at Google, ex-Amazon Location: Cambridge, Massachusetts, United States Profile: https://flows.cv/stevethomas ## Work Experience ### Senior Software Engineer @ Google Jan 2024 – Present | Boston, Massachusetts, United States ### Software Engineer - Resource Efficiency Data Science @ Google Jan 2022 – Jan 2024 | Boston, Massachusetts, United States ### Software Development Engineer - Alexa Edge Machine Learning @ Amazon Jan 2020 – Jan 2022 | Boston, Massachusetts, United States ### Software Engineer / Resident Deep Learning Expert @ Engine ML Jan 2018 – Jan 2020 | San Francisco Bay Area I worked with an impressive team of engineers to build a GPU-enabled distributed deep learning compute and experiment tracking platform. I mentored our clients’ ML and perception teams, helping to integrate their models and build pipelines with our platform and educating them on best practices as they transitioned from training on one to many GPUs. Using the data from these interactions, I worked with our team to design and program new products and features. Deep Learning Writings and Presentations: • Led research showing how layer-wise optimizers (e.g. LAMB) can train object detectors (e.g. Mask-RCNN) with large batch sizes in a fraction of the time without performance degradation. Results can be found on our company blog at https://bit.ly/35gfM0P. • Built a cat detector that was trained live in 5 minutes on 64 GPUs at VentureBeat Transform 2019 using a TensorFlow implementation of RetinaNet. The demonstration by our CEO can be found at https://bit.ly/2YdMbnr. Software Development Examples: • Led the design and programming effort of our local offering that allowed users to run deep learning experiments on their own hardware and compare the results in the Engine Dashboard alongside their cloud jobs. The product tracked and persisted code changes, logs, outputs, model performance metrics, system utilization metrics, and dataset metadata. Technologies include: Kotlin, Python, NGINX, PostgreSQL, Hasura, GraphQL, InfluxDB, Elasticsearch. • Designed and programmed an email alerting service that notified users when their experiments entered a terminal state. Technologies include: Kubernetes, Docker, Prometheus, PromQL, Python. • Designed and programmed a feature to pre-fetch training data from S3 buckets, storing it in an in-memory read-through cache using Alluxio and Alluxio’s FUSE-based POSIX API, resulting in up to a 5x speedup when reading a remote file. ### Independent Machine Learning Researcher @ Self Employed Jan 2016 – Jan 2018 I studied to become an ML expert by taking online courses, replicating papers, and learning by doing. Sample projects include: • “Top Contender” in The Lyft Perception Challenge 2018, a semantic segmentation competition, using a tweaked version of Google’s DeepLabV3 with ResNet-152 as the backbone (https://github.com/sathomas2/Lyft_Perception_Challenge). • Designed and integrated perception, behavior planning, trajectory generation, and controller modules so Udacity’s driverless car could safely navigate a road with traffic lights (https://github.com/sathomas2/CarND-Capstone-Solution). ### Business Development Consultant @ Inquizica Jan 2017 – Jan 2017 | Greater Philadelphia Area • Co-authored a business plan with CEO and CTO to expand the learning engagement platform to additional medical schools. • Offered insight on how to use machine learning to partially automate a quiz generator. ### Novelist @ Self-Employed Jan 2012 – Jan 2016 • Wrote three novels and several short stories, networking for years to sell them to top publishers. It was my full time job. After many close calls but no successes, I switched focus to software development with a particular enthusiasm for machine learning. ### Business Development @ WorldNow Jan 2014 – Jan 2015 | New York • Collaborated with chief officers to reposition and rebrand the company for what became a successful acquisition. • Wrote for industry journals to spread brand awareness during expansion into broader markets and secured awards like the 2015 NAB Show Product of the Year Award, 2015 BIG Innovation Award, and 2014 New Bay Media NewsTech Award. ### Traffic Manager @ TubeMogul Jan 2011 – Jan 2012 | Emeryville CA • Led operations on strategic online video advertising campaigns for major brands, such as Disney and Toyota. • Analyzed performance and pricing trends of hundreds of sites across ad exchanges to maximize key campaign performance metrics while exceeding internal margin goals. ## Education ### Self-Driving Car Engineer in Computer Science Udacity ### Deep Learning Nanodegree Foundation in Computer Science Udacity ### Masters of Interdisciplinary Studies in Philosophy New York University ### B.A. in English, Economics Bowdoin College ### English Theater British American Drama Academy ## Contact & Social - LinkedIn: https://linkedin.com/in/steveathomas - GitHub: https://github.com/sathomas2 --- Source: https://flows.cv/stevethomas JSON Resume: https://flows.cv/stevethomas/resume.json Last updated: 2026-03-31