Software Engineer

Michael James Schock

• Email: *@********.***

• GitHub: mjschock

• LinkedIn: in/mjschock

Education

Master Of Science In Computer Science @ Georgia Institute of Technology, Atlanta, GA, 2025

• CS 6603: AI, Ethics, and Society, Spring 2024

• CS 7646: Machine Learning for Trading, Fall 2023

• CS 7643: Deep Learning, Fall 2022

• CS 7639: Cyber-Physical Systems Design & Analysis, Spring 2021

• CS 7642: Reinforcement Learning & Decision Making, Fall 2019

• CS 7641: Machine Learning, Spring 2019

• CS 6601: Artificial Intelligence, Fall 2018

• CS 7638: Artificial Intelligence Techniques for Robotics, Spring 2018 Bachelor Of Arts In Physics @ University Of California, Berkeley, Berkeley, CA, 2010 Experience

Software Engineer (AI/ML Platform) @ Phaidra, Seattle, WA, Oct. 2022 - Jan. 2024

• Spearheaded orchestration and automation of AI agent training (with each agent an ensemble of PyTorch models) into an MLOps pipeline backed by a self-hosted in-cluster duo of Prefect Server and Agent to run training ad-hoc and on-schedule, with follow-up work demonstrating the migration path from the deprecated Prefect Agent to Kubernetes-native Prefect Worker.

• Rapidly prototyped a working MVP showcasing how we could easily scale the training runs via the Prefect-Ray integration and an in-cluster or Anyscale Cluster, also presenting SkyPilot as a way to abstract Ray and cloud computing resources, optimizing for minimal computational cost or time.

• Modernized the developer experience for the AI Platform team by bringing in Tilt to watch for changes in the Kubernetes manifests for full Docker build/pushes, thereafter updating pods without reload for fast iteration, and providing custom functionality to run data preparation, agent training, and inference pipelines via configurable buttons in the Tilt UI. Machine Learning Engineer @ Greyscale AI, San Carlos, CA, Oct. 2021 - Jul. 2022

• Created a proof of concept (POC) for a data engineering pipeline to extract, transform, and load images and their corresponding labels from various data sources and formats into the COCO dataset format with k-fold train-validation-test splits using the FiftyOne and Albumentations libraries.

• Constructed a POC for a data modeling pipeline to train and validate a PyTorch Faster R-CNN model with various modifications for computer vision tasks such as object detection and image segmentation from a train-validation split output by the data engineering pipeline.

• Assembled a POC for a model deployment pipeline to deploy a model produced by the data modeling pipeline into a local docker container running TorchServe (or SageMaker) to run inference tests upon that model and to trigger the creation of a function that ran on schedule to monitor the deployed model.

• Designed a dashboard using Amazon QuickSite to automatically generate visualizations, including emails pointing to those visualizations, that displayed the performance of the served model and assigned SageMaker GroundTruth jobs for our internal teams to help with data labeling.

• Built a POC framework using Kedro and DVC to join the data engineering, data modeling, and model deployment pipelines, running pipeline components only when artifacts tracked by DVC changed. 1

Machine Learning Engineer @ Ople.AI, San Mateo, CA, Sep. 2018 - Oct. 2021

• Refactored the data ingestion pipeline into more modular components.

• Drove the model explainability implementation.

• Led the development of the forecasting service.

• Built a worker service that operated on graph structures representing machine learning tasks and states.

• Developed various features and addressed bugs in our systems. Software Engineer @ BigCommerce, San Francisco, CA, Nov. 2016 - Sep. 2018

• Engineered features for the BigCommerce storefront platform.

• Wrote unit tests for all new and changed code, increasing code coverage.

• While taking the lead on building out a new feature, discovered an opportunity to improve the codebase by refactoring the code into an easier-toreason-about structure such that future additions wouldn’t require as much overhead.

Software Engineer @ Autodesk (via Globant), San Francisco, CA, May 2014 - Oct. 2016

• Implemented features for the Customer Enterprise Portal for Autodesk.

• Caught up to speed quickly, diving into the codebase with minimal support.

• Formed a POC to re-architect a centerpiece of the Portal, refactoring spaghetti code and building a more well-organized system that can easily accommodate new types of Autodesk products and services along with their associated data and functionality.

• Taught and led other developers with patience and a desire to improve their understanding.

• Responded to bugs, defects, and applicable business concerns with a strong sense of urgency. Software Engineer @ PlantLog, Pleasanton, CA, Aug. 2012 - May 2014

• Converted features from the legacy implementation of PlantLog, which ran only on Windows as a native application, to a web and mobile application hosted in the cloud. Re-architected the backend to be RESTful, refactoring a single large switch case into resource-specific endpoint logic.

• Converted legacy reporting components for use in the new system.

• Rebuilt the mobile app, using the BackboneJS framework to organize the application.

• Added barcode scanning/lighting functionality to the mobile app. Projects

• Generative AI Nanodegree (Udacity), May 2024

• Multi AI Agent Systems with crewAI (DeepLearning.AI), May 2024

• Prefect Associate Certification (Credential ID: 72680269), Apr. 2023

• Machine Learning Engineer Skill Set Certification (Workera; Credential ID: 4JKAZBKL), Aug. 2022

• Deep Reinforcement Learning Nanodegree (Udacity; Credential ID: CKU3QGTF), Jul. 2019

• Math for Machine Learning Specialization (Coursera; Credential ID: RE4TKCWC7U6X), Jan. 2019

• Deep Learning Part I Certificate (The Data Institute, University of San Francisco), Dec. 2018

• Deep Learning Specialization (DeepLearning.AI, Coursera; Credential ID: P234NUS9DS7M), Sep. 2018

• Deep Learning Foundation Nanodegree (Udacity; Credential ID: 6LD4H74U), Jan. 2018

• Artificial Intelligence Nanodegree and Specializations (Udacity; Credential ID: EH367J99), Oct. 2017

• Machine Learning Specialization (Coursera; Credential ID: S58WYDFTRMTB), Feb. 2017

• CSCI E-160: Java for Distributed Computing (Harvard Extension School), 2012 Skills

• crewAI, LangChain, LangGraph, LlamaIndex, Prefect, PyTorch, Ray, SkyPilot, Transformers, . . . 2

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