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Currently Machine Vision Software Engineering Intern Tesla, Vision Systems

Adam Dabees

I build and debug systems where failure is expensive: machine vision on live production hardware, distributed infrastructure, and the tooling that keeps both honest.

Get in touch Available May – Aug 2027
3.91 / 4.00
GPA, top 1% of cohort
30K+
monthly users served in production
<100 ms
at 1,000+ concurrent connections
01

About

I write software for systems where being wrong is expensive: vision pipelines running on a moving production line, platform infrastructure at a $247B pension fund, services that have to stay up while traffic triples.

Most of what I'm good at is diagnostic. Working out which layer a failure actually lives in (application, container, network, or the camera itself) is usually harder than the fix, and I've gotten fast at it. The rest of the job is building the tooling so the same problem doesn't need a person the next time it shows up.

Right now that's machine vision at Tesla. Before that, distributed platform work at Ontario Teachers' Pension Plan and a few years of shipping things real users depended on. Outside of that I founded McMaster's self-driving car club, where we're building a ROS perception stack from the ground up.

Based in
Palo Alto, CA
Focus
Machine vision, distributed systems, infrastructure
Open to
May – Aug 2027
02

Experience

  1. Tesla

    Aug 2026 – Present

    Machine Vision Software Engineering Intern

    Vision SystemsPalo Alto, CA

    • Develop and improve machine vision systems for automated defect detection on live production hardware: image processing pipelines, camera and lighting configuration, and detection accuracy measured against labeled failure cases.
    • Debug system-level failures on high-volume production lines alongside controls and process engineering, tracing faults across software, camera hardware, and network layers.
    • Analyze image and production data to find where inspection accuracy breaks down, then feed those cases back into detection logic.
    • Write Python and shell tooling that automates inspection, validation, and production data analysis for the engineering team.
  2. Ontario Teachers' Pension Plan

    May 2026 – Aug 2026

    Software Engineer (Co-Op)

    $247B AUM, Canada's largest single-profession pension fundToronto, ON

    • Built Python AI agents and MCP-based systems that replaced manual log inspection with automated anomaly surfacing across a large internal codebase.
    • Deployed and operated containerized services on Kubernetes (AKS) with Docker: rollout config, resource requests, and scaling behavior for internal platform workloads.
    • Debugged production issues across distributed services using Dynatrace distributed tracing, isolating faults spanning application, container, and network layers.
    • Automated provisioning with Terraform and Ansible, replacing manual setup with consistent, auditable environments across 5+ internal services.
    • Shipped through Jenkins CI/CD pipelines covering build, automated test, and release.
  3. Brandeck Egypt

    Jan 2025 – May 2026

    Software Developer (Contract)

    E-commerce platformRemote

    • Built distributed AWS Lambda and DynamoDB pipelines serving 30K+ monthly users, cutting end-to-end latency 80% and compute cost 35% through request batching and better I/O patterns.
    • Added idempotent writes, exponential-backoff retries, and rate limiting to absorb 3× traffic spikes without unplanned downtime.
    • Established structured logging, distributed tracing, and alerting that cut average incident resolution time 50%.
03

Selected work

Things I built end to end. The numbers are measured, not estimated.

LiveCategories

Real-time multiplayer platform2024

A real-time distributed platform running on Kubernetes, holding 1,000+ concurrent connections at sub-100ms latency over persistent WebSocket/TCP sockets. Kafka handles inter-service event streaming; request routing and horizontal autoscaling keep throughput steady across replicas under load.

  • Kubernetes
  • Docker
  • Kafka
  • PostgreSQL
  • WebSockets
  • FastAPI
  • Next.js

ResumeMatcher Pro

LLM inference platform2025

Scores resume-to-job compatibility and returns structured gap analysis over a RESTful API. The inference layer runs as its own FastAPI service, decoupled from the frontend so the serving path scales independently, and end-to-end response holds under 2 seconds. Includes LaTeX editing that folds job-specific keywords back into the source document.

  • Python
  • FastAPI
  • Groq LLM
  • Next.js 15
  • LaTeX
  • Vercel

Shopifly

E-commerce monitoring & automation2025

Tracks product availability across arbitrary online stores and executes automated purchases. A WebSocket-driven queue dispatches Playwright browser jobs across AWS Lambda, with DynamoDB persistence, Cognito auth, and Stripe subscription tiers behind API Gateway.

  • Next.js 15
  • AWS Lambda
  • DynamoDB
  • API Gateway
  • Playwright
  • Stripe
  • Cognito

Rescue Mission

Island exploration engine2024

An exploration command center for the Island serious game: Java game logic on Maven, with map exploration, point-of-interest detection, and the decision algorithms that drive search strategy under a fuel budget.

  • Java
  • Maven
  • Algorithm Design
  • JUnit

Revenge of the Recycling System

Systems analysis2024

System design and data analysis on recycling and waste-management processes, working from measured throughput rather than assumptions about where the losses were.

  • System Design
  • Data Analysis
  • Modeling
04

Stack

Grouped by what it's actually for, not by how it looks on a keyword filter.

Languages

  • Python
  • C/C++
  • Java
  • TypeScript
  • JavaScript
  • SQL
  • Bash/Shell

Systems & Networking

  • Linux
  • Concurrent multi-process programming
  • Real-time systems
  • Computer architecture
  • TCP/IP & sockets
  • Memory and caching behavior
  • Low-level debugging

Containers & Infrastructure

  • Kubernetes (AKS)
  • Docker
  • Microservices
  • Autoscaling
  • Azure
  • AWS (Lambda, DynamoDB, S3, EC2, API Gateway)
  • OpenStack
  • Terraform
  • Ansible

ML & Vision

  • Computer vision
  • Image processing
  • Real-time inference pipelines
  • Model evaluation
  • LLMs & LLM serving (Groq)
  • AI agents
  • Model Context Protocol
  • ROS perception

Data & Storage

  • PostgreSQL
  • DynamoDB
  • Firestore
  • Redis
  • Kafka
  • Query optimization
  • Caching
  • Data pipelines

Tooling & Practice

  • Git/GitHub
  • Jenkins
  • CI/CD
  • Dynatrace
  • Distributed tracing
  • Performance analysis
  • Test design
  • Code review
  • Agile
05

Leadership

Founder

McMaster Self-Driving Car Club

Jan 2025 – Present

Started the club and grew it to 20+ members, building a ROS perception stack on Linux: real-time camera pipelines, publish/subscribe messaging between concurrent processes, and simulation-based edge case validation against labeled failure scenarios.

President

McMaster Egyptian Student Association

Sep 2024 – Present

Run a 25-person exec team across marketing, finance, and operations. 8+ events delivered for 1,000+ attendees, and a rebuilt planning process that cut event overhead 30% after tracking where the time and budget were actually going.

06

Education

McMaster University

Sep 2023 – May 2028 (Expected)

B.Eng. Software Engineering (Co-Op)

Hamilton, ON

  • 3.91 / 4.00 GPA, top 1% of cohort
  • Admitted under Free Choice Admission, top 1% of all applicants

Relevant coursework

  • Computer Architecture
  • Real-Time Systems
  • Distributed Systems
  • Data Structures & Algorithms
  • Database Systems
  • Machine Learning
  • Software Design