Max Newcomer



University of Wisconsin – Madison

Bachelor of Science - Computer Science, Mathematics, and Data Science

(09/2019 - 12/2022)

Courses - Operating Systems, Algorithms, Matrix Methods in Machine Learning, Linear Optimization, Machine Organization, Databases



Mid-Level Software Engineer

(May 2023 - Present)

  • Led the end-to-end development of a comprehensive full-stack web application for our largest agency client, overseeing scope, timelines, and communication with the client’s senior leadership.
  • Ensured the security and durability of client documents, implementing Disaster Recovery plans to minimize Recovery Time Objective (RTO) and Recovery Point Objective (RPO).
  • Architected, maintained, and documented a critical business service from the ground up, while managing both internal and external Service Level Agreements (SLAs).
  • Designed and built advanced document processing pipelines utilizing embeddings, vector databases, and self-hosted Large Language Models (LLMs).
  • Improved document processing runtimes by 6.5x through a zero-downtime transition to auto-scaling queue consumers.
  • Spearheaded the development team’s observability initiative, establishing comprehensive logging, tracing, and profiling for frontend, backend, and ML repositories, all integrated into a centralized log management service.


Software Engineering Consultant

*(Jan 2023 - May 2023)

  • Provided consulting services to a growing brand to enhance their SEO rankings. Leveraged data from common SEO tools to develop forecasting models for keyword optimization, resulting in a 10,000 page view increase over 2.5 months.
  • Designed and implemented sophisticated algorithms to calculate Total Addressable Market (TAM) and Serviceable Available Market (SAM) using SEO and Google Traffic analytics. Collaborated closely with clients to align these metrics with their business objectives, providing strategic insights for vertical market development.

United States Geological Survey (USGS)

Software Engineer (Student Team Leader, Part-Time)

(May 2019 - Jan 2023)

  • Constructed software as described in NWTOPT publication that is used by hydrologists globally for distributed Tree Parzen Estimator hyperparameter optimization for MODFLOW-NWT model solver settings, resulting in an average of ∼80% run time reduction of model solves. This has saved the USGS months worth of on-prem computation.
  • Led and mentored a junior developer, delegating tasks and ensuring timely and accurate completion of project milestones in alignment with our team’s roadmap. Facilitated effective collaboration and problem-solving, enhancing overall project efficiency and productivity.
  • Trained Generative Adversarial Networks (GANs) to generate physically-realistic realizations of hydro-geological conductivity maps derived from sparse observational-data and hydrologist-informed hypotheses of conductivity distributions.


Software Engineer Intern (Part-time)

(Jun 2020 - Dec 2020)

Publications & Presentations

NWTOPT - A Hyperparameter Optimization Approach for selection of Environmental Model Solver Settings (Newcomer, Hunt, 2022)

Published in the journal of Environmental Modelling & Software -

MODFLOW and More (Newcomer, Hunt, 2022)

NWTOPT research accepted to the MODFLOW and More conference, a MODFLOW, water system, and machine learning conference at Princeton University.

Skills Summary

  • Languages: Go, Rust, Python, C/C++, SQL, JS/TS, R, Java
  • ML Tooling: Langchain, Scikit, TensorFlow, Keras, Lambda Stack, Weights & Biases, MLFlow, ClearML
  • Cloud: AWS, ECS, Fargate, Lambda, SNS, SQS, Kinesis, MSK, Cloudformation, Networking, Azure AD
  • Other: Docker, Git, PostgreSQL, MySQL, DynamoDB, SQLite, Datadog
  • Soft Skills: Collaborative Team Member, Effective Communicator, Creative Problem-Solver

Last updated on 06/24/2024

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