Hi, I’m Maya Devarajan.

MBSE Software Architect • Seattle, WA

I’m passionate about using data and machine learning to solve meaningful challenges and drive smarter decisions. I love working with curious, forward-thinking teams where technical depth meets creative problem-solving.

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About

I’m driven by the challenge of using data and machine learning to create meaningful impact in complex, real-world settings. I’m especially motivated by work that sits at the intersection of data, technology, and collaboration — where analytical rigor meets creative problem-solving. I’m interested in opportunities in data science, ML engineering, or analytics that allow me to apply technical depth, foster innovation, and contribute to teams shaping the future of intelligent systems.

Experience

MBSE Software Architect · Dassault Systèmes

2024–Current · Seattle, WA

Skills
- Product Architecture
  - Define and maintain product architecture across structural, behavioral, and requirements views
  - Translate stakeholder needs into traceable system designs using MBSE processes and tooling
- MBSE Processes
  - Establish and govern modeling workflows, standards, and review processes across teams
  - Drive consistency in how architecture artifacts are authored, versioned, and validated
- Data & ETL
  - ETL pipelines to extract, transform, and load engineering models
  - Feature engineering from architecture artifacts for analytics
- Analytics Methods
  - Uncertainty quantification and sensitivity analysis for KPIs
  - Data-informed decisions under system variability
- Tools & Languages
  - Python, SQL; PyTorch; Web services
Vaccine Manufacture Data Analytics Intern · Merck & Co., Inc.

Jun 2024–Aug 2024 · West Point, PA

Skills
- Analytics & BI
  - Power BI, Power Query, DAX, SQL for quality/compliance ops
  - Dashboards for disinfection monitoring and sample status
- Solutions Delivered
  - Three production-ready solutions to improve efficiency
  - Quality notification and manufacturing workflow improvements
- Data Engineering
  - Automated transformations and pipeline optimization
  - Improved dashboard responsiveness and maintainability
Machine Learning Researcher — Cornell Tech

Jan 2022 — Aug 2023 · Ithaca, NY

Skills
- NLP & Privacy
  - BERT-based de-identification for electronic health records (EHRs)
  - Natural Language Processing for medical text
- Modeling & Evaluation
  - Model monitoring with black-box pipelines in PyTorch
  - Cross-validation, metrics, and statistical analysis
- ML Stack
  - Python, PyTorch; model fine-tuning and regularization
Machine Learning Undergraduate Researcher · Cornell University

Jan 2022 — May 2022 · Ithaca, NY

Skills
- Bioimage ML Research
  - Developed and trained a neural network to segment and classify dendrite growth in neurodegenerative disease bioimages for a microbiology lab project
- Data Preparation
  - Used Fiji and related image analysis tools to build ground-truth datasets for model training
- Model Development
  - Coded and fine-tuned a UNet segmentation model in TensorFlow for high-accuracy segmentation
- Research Workflow Integration
  - Implemented the final model in the lab workflow to streamline analysis and support neurodegenerative disease research

Projects

Clinical Reasoning Sandbox

Multi-agent LLM orchestration pipeline for clinical case reasoning: structured intake → differential diagnosis → parallel evidence and risk assessment → management planning → critic safety layer (PASS / REVISE / BLOCK) → narrative synthesis. Features a React + ReactFlow UI with real-time SSE streaming, an interactive workflow graph, and an inspector panel for artifact trace export. Runs fully local via Ollama.

Python • FastAPI • React • TypeScript • Ollama • asyncio • SSE • ReactFlow

Code

Contact

Interested in working together? Reach out via email or connect on LinkedIn.