Available for remote, entry-level ML / AI engineering roles

Andrew Allen

Product-minded builder transitioning into applied AI/ML. I ship software, learn fast, and focus on correctness, performance, and clear communication—using projects and coursework as the primary proof of capability.

Email Andrew View projects

Highlights

A few high-signal proofs and strengths

Shipped software

Built and shipped iOS apps as a solo developer, working through real-world UX, performance, and reliability constraints.

Algorithmic + systems mindset

Comfortable reasoning about data structures, complexity tradeoffs, OS scheduling effects, and concurrency.

Structured upskilling

Active AI/ML learning through Coursera, Microsoft Learn, and math practice focused on statistics and probability.

Selected Projects

Proof over chronology

Pxlz — iOS pixel art app

What it is: A fingerpaint-style pixel art workflow, shipped via a personal App Store account.

What I did
Solo development; designed the interaction model, implemented core algorithms, and optimized for responsive drawing.
Stack
Swift, UIKit (with prior Objective-C experience in the pre-Swift era).
Outcome / artifact
Shipped iOS app (public listing details not included here).
iOS Swift UIKit Algorithms Performance

Metronome — iOS timing accuracy app

What it is: A metronome app designed for high timing accuracy on iOS (challenging under OS scheduling).

What I did
Implemented timing logic and mitigations for background interference; worked with parallel threading for reliability.
Stack
iOS (language/framework details not claimed here).
Outcome / artifact
Brought to market (App Store details TBD).
iOS Concurrency Timing Reliability

Arkanoid / Brick Breaker — Java game

What it is: A classic arcade-style game built in Java as part of a Stanford open-source CS course.

What I did
Hand-coded animation logic and gameplay physics; built an interactive loop with responsive controls.
Stack
Java
Outcome / artifact
Course project (public artifact not linked here).
Java Physics Animation Game loop

PowerShell automation lab (self-directed)

What it is: A set of practical scripts and lab workflows supporting server admin and networking practice.

What I did
Built scripts for system inventory/diagnostics, storage cleanup, and repeatable environment tweaks; configured local VM networks for labs.
Stack
PowerShell, Windows/VM networking labs
Outcome / artifact
Working scripts and repeatable lab setups (not published).
PowerShell Automation Networking Virtualization

RAG solution with custom data (in progress)

What it is: A learning build focused on retrieval-augmented generation patterns using Microsoft Learn content.

What I did
Working through hands-on modules: planning and building a RAG-based solution with user data (in progress).
Stack
Microsoft Learn (Azure AI / Foundry learning path; module work in progress).
Outcome / artifact
In progress; not claiming results until completed and documented.
RAG LLMs Azure AI (learning) Responsible AI

Experience

Curated to support AI/ML + engineering narrative

Independent software development

Shipped iOS applications as a solo developer, with emphasis on real-world performance, correctness, and user interaction.

  • Designed and implemented core algorithms and data models for interactive features.
  • Worked through performance constraints and complexity tradeoffs to keep apps responsive.
  • Used concurrency and timing strategies where reliability mattered.

Self-directed AI/ML upskilling

Building ML foundations with structured coursework and deliberate practice—prioritizing statistics and probability.

  • Coursera: Generative AI & LLM architecture/data prep; quantitative modeling foundations.
  • Microsoft Learn: AI Fluency trophy; core modules in AI basics, responsible AI, and Azure AI planning.
  • Brilliant: ongoing math refresh (probability, linear algebra, calculus) to support ML rigor.

IT labs & scripting (coursework + practice)

Practical experience with Windows Server administration topics, networking, virtualization, Linux, and automation via PowerShell.

Skills

Grouped for clarity

AI / ML foundations

  • Machine learning & AI basics (actively strengthening)
  • Deep learning basics (foundational)
  • Responsible AI concepts (coursework)
  • Math focus: statistics & probability (in progress)

Software engineering

  • iOS development: Swift, UIKit
  • Java (course/project work)
  • Algorithms, data structures, complexity tradeoffs
  • Concurrency/threading concepts (applied in iOS projects)

Automation & systems

  • PowerShell scripting/automation
  • Windows Server admin topics (labs/coursework)
  • Networking & virtualization labs
  • Linux familiarity (labs/coursework)
  • Security fundamentals (coursework)

Education & Certifications

Included where it strengthens positioning

Education

  • Mitchell Technical College — AAS, Business Management (Graduated May 2011)
  • Dakota State University — AI-related coursework (Spring & Summer 2025; topics remembered: AI, statistics, linear algebra, discrete math, CS)
  • Mitchell Technical College — additional study (partial): IT (Windows Server administration, scripting, networking, virtualization, Linux); SCADA (1 semester)

Selected coursework / credentials

  • Coursera (IBM) — Generative AI and LLMs: Architecture and Data Preparation (Completed Jan 2026)
  • Microsoft Learn — AI Fluency trophy (account: AndrewAllen-8471)
  • Coursera (University of Pennsylvania) — Fundamentals of Quantitative Modeling (Completed Aug 2024)
  • Coursera (Cisco) — SOC (Sep 2025) + Security series (Oct 2025)

Note: Some learning items are ongoing; only completed or clearly documented items are listed as such.

Contact

Best way to reach me: email

Get in touch

I’m looking for remote, entry-level ML/AI engineering roles where I can contribute through strong fundamentals, shipped software, and consistent learning velocity.