// ALEJANDRO_ARTEAGA

> whoami

Alejandro Arteaga

Robotics & systems software engineer. I work on autonomous systems, edge AI, and the infrastructure that verifies them.

Currently an M.S. Computer Science (Intelligent Robotics) student at USC and a Software Infrastructure Intern on NVIDIA's Autonomous Vehicles V&V team. Background spanning underwater robotics, 5G modem testing automation, and computational physics.

[ GITHUB ] [ LINKEDIN ] [ RESUME.PDF ↓ ]
01

[ EXPERIENCE ]

ACTIVE

Software Infrastructure Engineer Intern @ NVIDIA

Autonomous Vehicles — Verification & Validation · Santa Clara, CA

Building software infrastructure for the Autonomous Vehicles Verification & Validation team — tooling and pipelines that exercise and validate AV software at scale.

IMPACT
  • Data-governance tooling that quantifies labeled-data quality with precision/recall metrics
  • Agentic data-mining loops that iteratively refine strategies to surface rare driving scenarios from large-scale fleet data
  • Infrastructure bridging engineering and ML workflows, cutting manual data-curation effort across the AV org
  • Python
  • Data Infrastructure
  • Agentic Tooling
  • Autonomous Vehicles
  • V&V

Software Engineer Intern @ Qualcomm

Modem Software — 5G Access Stratum Automation, Integration & Test · San Diego, CA

Developed automation for 5G Access Stratum modem software integration and test, streamlining validation workflows for the modem software team.

IMPACT
  • Modular Python test-case extractor parsing 5G logs into a searchable SQL database — rapid developer testing against 10,000+ daily test cases
  • Resolved a critical race condition in the multiprocessing cloud upload pipeline, ensuring reliable capture of all test execution data
  • Strict schema enforcement during log parsing surfaced latent testing-framework bugs, improving 5G test-case validity
  • Python
  • 5G
  • Jenkins
  • SQL
  • Automation
ACTIVE

Senior Robotics Software Engineer @ USC RobosubSC

Autonomous Underwater Vehicle Design Team · Los Angeles, CA

Leading software for USC's autonomous underwater vehicle — orchestration, motion planning, and sensor fusion on a Jetson-based ROS stack.

IMPACT
  • K3s Kubernetes cluster across a Jetson–Raspberry Pi network orchestrating containerized ROS nodes
  • Custom 3D RRT motion planner with dynamic obstacle avoidance and cubic-spline smoothing for 6-DOF control
  • WaterLinked DVL A50 ROS driver feeding acoustic-IMU data into an EKF-based 3D-SLAM system
  • 99.9% IMU data reliability after diagnosing serial failures (dmesg, lsusb) and hardening udev rules
  • ROS
  • K3s Kubernetes
  • Motion Planning
  • SLAM
  • Jetson
  • C++

Robotics Software Engineer @ CMU TartanAUV

Autonomous Underwater Vehicle Design Team · Pittsburgh, PA

Developed software for Carnegie Mellon's autonomous underwater vehicle — perception, controls, and mission autonomy on a ROS-based robotics stack.

IMPACT
  • Depth-camera simulation in ROS Gazebo enabling obstacle-avoidance autonomy testing
  • 3,000+ annotated bounding boxes expanding the CenterNet object-detection training set
  • Arduino–Jetson battery-monitor firmware with safety shutdowns preventing power failures
  • HSV color-detection pipeline processing RGB feeds at 30 FPS, published to RViz
  • C++
  • ROS
  • Gazebo
  • OpenCV
  • Arduino

Software Engineer Intern @ National Instruments

Telemetry Squad · Austin, TX

Contributed to the Telemetry Squad, building and improving telemetry data collection and tooling for NI's software platform.

IMPACT
  • Containerized ETL pipeline prototyped on a distributed Spark cluster for an analytics model
  • 90% ETL runtime reduction by caching Mongo batches in schema-enforced PostgreSQL
  • 30% throughput improvement for large-scale workloads by benchmarking four cluster architectures
  • Python
  • Apache Spark
  • PostgreSQL
  • MongoDB
  • ETL

Scientific Computing Research Assistant @ CMU Physics — Neutrino Group

Mellon College of Science · Pittsburgh, PA

Supported neutrino physics research with scientific computing — data pipelines and numerical analysis for experimental physics workloads.

IMPACT
  • 90% speedup of photodetector waveform analysis via C++ multithreading (Michel-electron distributions)
  • Calibrated photosensor energy readings on a heavy-water detector against simulated distributions
  • Quantified magnetic-field effects on photosensor geometry, improving physics-simulator accuracy
  • C++
  • Python
  • HPC
  • Scientific Computing
02

[ EDUCATION ]

University of Southern California

M.S. Computer Science — Intelligent Robotics

USC Viterbi School of Engineering · Los Angeles, CA

Expected Dec 2026. GPA 3.7/4.0 — University GEM Fellow, Hispanic Scholarship Fund Scholar.

Carnegie Mellon University

B.S. Physics / Astrophysics, Minor in Computer Science

Mellon College of Science · Pittsburgh, PA

03

[ PROJECTS ]

Multimodal GenAI Nutrition Assistant

★ FEATURED

SYSTEMS

Personal nutrition assistant running entirely on-device: Snapdragon inference of the Gemma 3 multimodal model over smartphone food photos and text prompts, with a retrieval-augmented-generation backend on a FAISS vector database for accurate nutritional analysis. Built at the Qualcomm Edge AI Developer Hackathon.

  • Python
  • GenAI
  • RAG
  • FAISS
  • On-Device Inference
  • Edge AI
> REPO

DLIO Edge Optimization

★ FEATURED

ROBOTICS

Benchmarked real-time performance of Direct Lidar-Inertial Odometry (DLIO) on an NVIDIA Jetson AGX Orin, demonstrating its viability for high-sampling-rate, low-memory-footprint localization and mapping on edge hardware. Profiled CPU load, core utilization, memory footprint, and computation time across the multi-threaded pipeline, isolating the key performance bottleneck in the Generalized-ICP scan-matching step.

  • C++
  • ROS
  • SLAM
  • LiDAR
  • Jetson
  • Edge Computing
  • Profiling
> ANALYSIS > BENCHMARK FORK