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Resume

·475 words·3 mins
Table of Contents

Lockheed Martin
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  1. Machine Learning Engineer

    Apr 2022 - Present

    Staff AI Research Engineer

      Internal Consulting

      Worked within the internal AI consulting team to create generative code products that save the company millions of dollars each year, and ensure that program codebases can be shipped to customers and into space.

      Content Creation

      Created tutorials, publications, and demonstrations to aid over 8,000 developers in the internal AI community, garnering over 26,000 views across all posts from within the company. Content included the following topics:
      • The MLOps cycle using KubeFlow Pipelines, Python, Rust, and Golang tooling.
      • AI solution architectures for patterns of common problems across the enterprise, including business and mission use cases.
      • Model serving using TorchServe, TFServing, ONNXRuntime, KServe, and Ray.
      • Best practices for using distributed model training, serving, and LLM utilization.
      • End-to-end application deployment using Kubernetes and AWS.

  2. Machine Learning Engineer

    May 2021 - Apr 2022

    Senior ML Engineer

      Extractive Text and Chat

    • Independently led policy design, implementation, and deployment of an enterprise suite of AI chat applications through the entire software development and machine learning life cycles.

      • Data Engineering

    • Gathered and integrated original content from company policies and procedures to implement extractive summarization models using TensorFlow, PyTorch, and HuggingFace.

      • Deployment

    • Single-handedly designed, maintained, and deployed applications using OpenShift and Istio to provide an application offering across multiple business areas to thousands of users.

Independent Consulting
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  1. Consultant

    Oct 2018 - May 2021

    SW/ML Engineer

      Data Analysis in Recruiting

    • Performed statistical analysis and visualization work for a recruiting and placement company, allowing them to apply cost of living adjustments to placed employee salaries across the United States.
    • Created and deployed web applications for various data analysis use cases across commercial domains.

Projects
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  1. ML Applications

      Staffocaster

    • Predictive Staffing as a Service using time series modeling, Svelte JS, Terraform, and AWS to reduce manpower costs for clients.

      • Whitehouse RAG

    • Architected a Retrieval Augmented Generation development sandbox using a custom scraped dataset of published content from the administration of multiple US Presidents.

      • DayTripper

    • Built a fully automated AI Travel Agent, including a SvelteJS frontend, with Postgres, FastAPI, and swappable Phi4 Ollama backend

      • FormGen

    • Produced a full-stack web app using TypeScript React (TSX), Golang, Minio, and Postgres to convert PDF files into permanent, generated TSX form components.

      • Whisperer

    • Created a containerized, K8s deployable web app for transcription of audio files to text using OpenAI’s Whisper SDK and FastAPI.

  2. Personal Cloud

      Initialized K3s on a cluster of TuringPis and Raspberry Pis to create and deploy machine learning models and simulate developing cloud applications at zero-cost.

      Infrastructure

      Ansible managed deployments:
      • Monitoring with VictoriaMetrics, OpenTelemetry, and Grafana
      • Ingress with Traefik
      • TLS/SSL with CertManager, LetsEncrypt, and CloudFlare
      • Distributed storage with Longhorn
      • Object storage with Minio
      • Baremetal loadbalancing with Metallb
      • GitOps deployment tracking with ArgoCD
      • Cluster workflows and events with Argo Workflows and Events
      • AWS service development environment with LocalStack
      • Weaviate vector database