Nathan Baune
Backend & Platform Engineer
Technical Stack
Summary
Backend and platform engineer with 7+ years building distributed systems, real-time engines, and database architectures across industry, research, and independent R&D. Currently employed as software engineer in research while building an interactive storytelling platform (MUSE) in off-hours.
Seeking remote backend or platform engineering roles where I can contribute to production systems architecture, distributed systems design, and backend infrastructure. Available for 2-3+ year commitment; transparent about long-term goals.
- End-to-end ownership: architecture, implementation, databases, runtime, observability
- Systems depth: C++ simulation engines, Go backends, GPU compute, real-time processing
- Platform thinking: schema-driven architectures, code generation, control planes
- Production experience: NIH-funded research systems, SBIR-funded startup, active clinical use
Experience
SOFTWARE ENGINEER · Precision Neural Engineering Lab, Emory University 2021–Present
Backend systems engineer building research platforms, ML pipelines, and experimental control systems for NIH-funded clinical research. Lead engineer responsible for platform architecture, database design, and multi-modal system integration.
- Built MR.Flow: neuroimaging pipeline orchestration handling hundreds of subjects with multimodal scans, automated DICOM-to-BIDS conversion, parallel Docker execution. Reduced processing from 8+ hours to 45 minutes. Adopted by multiple labs. Python · PyQt6 · Docker · BIDS
- Built ePOCHE: ML signal-processing pipeline for EEG, IMU, EMG, and GSR with SQLite-backed experiment tracking, 11 classifiers, cross-validation reporting, and full reproducibility. Supporting active R01-funded clinical research. Python · PyQt6 · scikit-learn · TensorFlow · SQLite · MNE-Python
- Built closed-loop neurofeedback system: Real-time EEG artifact rejection with <50ms latency enabling adaptive experiment control based on brain state. Integrated with fMRI for multimodal closed-loop experiments. Python · C++ · MATLAB · Lab Streaming Layer
- Architected multi-modal integration framework coordinating VR, robotics, biosensors, and neuroimaging with sub-millisecond event marking precision. Lead engineer across 3+ labs for NIH-funded research. Python · C++ · MATLAB · Simulink · LSL
FOUNDER & LEAD ENGINEER · Gothic Grandma LLC 2025–Present
MUSE Living Worlds: Interactive Storytelling Platform
Building interactive storytelling platform where narratives emerge from biological character simulation rather than scripted events. Developing in off-hours while employed full-time.
Target scale: 100,000+ simulated characters with biological needs, psychological states, and social relationships. LLMs translate simulation state into natural language across 42 languages.
Platform Architecture
- C++20 simulation engine: GPU kernel batching with structure-of-arrays layouts, deterministic execution with explicit scheduling, 100k+ entity scalability, heterogeneous CPU/GPU execution. C++20 · CUDA · Metal · Vulkan
- Go backend: PostgreSQL persistence with row-level security, remote-first with retry queues, WebSocket real-time collaboration, async job queues, multi-tenant Auth/RBAC. Go · PostgreSQL (Supabase) · JWT · OAuth
- PostgreSQL-to-code pipeline: Visual schema editor (Constructor) enabling non-programmers to design biological/psychological systems → automated C++ kernel generation → compiled execution. PostgreSQL · Python · C++ codegen
- Multi-surface architecture: CYPHER (R&D workbench), CLIO (development management with Go backend and Python subprocess capability for LLM-integrated tooling), GLYPH (e-reader), CALLIOPE (marketplace). Cross-platform desktop (macOS, Linux, Windows). Electron · React · Flutter · Dart · Python · Go
Key Systems Design
- Unified all entity types under single kernel execution model using exclusion-based system masks
- Eliminated per-frame entity filtering via event-driven kernel membership updates
- Designed VRAM-backed detail tables shared across kernels preventing data duplication
- Implemented deterministic stepping, snapshotting, and replay for debugging and time-travel inspection
Status: Platform foundations implemented; targeting late 2027 for initial Living World launch. Available for full-time employment during multi-year development cycle.
CO-FOUNDER & TECHNICAL LEAD · PlatformSTL LLC 2017–2021
Proprio: Wearable Activity-of-Daily-Living Monitoring Platform
Co-invented Apple Watch IMU-based activity tracking system for stroke rehabilitation. Led technical direction, data infrastructure, clinical validation design, and ML pipeline.
- Built real-time streaming: Apple Watch IMU (30Hz 6-axis) → iOS app with packet queue preventing dropped packets → AWS Lambda processing → MongoDB storage → activity classification with <500ms latency. Swift · CoreMotion · AWS Lambda · MongoDB
- Designed ML pipeline: time-series feature extraction (sliding windows, FFT) → patient-specific model training → clinical deployment achieving 85-92% accuracy across 12 activity classes. Python · scikit-learn · pandas
- Built data operations: C# pipeline converting MongoDB to Python data structures, automated quality checks, handling 50GB+ sensor data. C# · Python
- Deployed in clinical validation studies with multiple stroke patients demonstrating system feasibility and accuracy
- Secured $100K SBIR grant from NIH. Published peer-reviewed validation results.
Education
PhD — Rehabilitation & Participation Science (Neuroscience Specialization), Washington University in St. Louis · 2020
BS — Experimental Psychology, University of Oregon · 2013