Senior ML Engineer

Christine Straub

Senior ML Engineer — AI Systems Architecture — MLOps

949-***-**** # ****************@*****.*** ï straubchristine § christinemstraub christinemstraub San Clemente, CA

Summary

Senior AI Engineer with 8+ years building production-scale AI systems, specializing in backend AI services, distributed systems, and real-time AI processing. Expert in LLM integration, fault-tolerant architectures, and data transformation pipelines. Deep expertise in asynchronous workflows, streaming architectures, and enterprise AI solutions.

Technical Skills

Areas of Expertise: Deep Learning, Machine Learning, Generative AI, Large Language Models (LLMs), Computer Vision, MLOps, Natural Language Processing (NLP), Reinforcement Learning, Multi-Agent Systems, Model Fine-tuning, Prompt Engineering, RAG, Context Engineering, System Architecture Programming Languages: Python, Rust, SQL, C/C++, JavaScript, TypeScript Programming Platforms: CUDA, JAX

AI/ML Frameworks: PyTorch, TensorFlow, Keras, Scikit-learn, FastAI, Hugging Face Transformers MLOps & Workflow: MLflow, Metaflow, Weights & Biases, DVC, Kubeflow, Model Monitoring Computer Vision: YOLO v8/v9, OpenCV, FiftyOne, Encord, PaddleOCR, Tesseract, Detectron2 NLP & Generative AI: LangChain, LangFlow, LlamaIndex, RAG, Prompt Engineering, OpenAI GPT-4/4o/3.5, Claude 3.5, Gemini Pro, LLaMA 3, DALL·E, Stable Diffusion, NLTK, SpaCy, Transformers, AutoGen, LoRA, QLoRA Data Engineering & Analytics: Pandas, NumPy, Matplotlib, PySpark, Apache Airflow, Snowflake, Databricks Database Systems: PostgreSQL, MongoDB, Vector Databases (Pinecone, Faiss, Chroma DB, Weaviate), Redis, Elasticsearch Cloud & Infrastructure: AWS (S3, EC2, Lambda, RDS, SageMaker, Bedrock), GCP (Vertex AI, BigQuery, AutoML), Kubernetes, Docker, CI/CD Pipelines, GitHub Actions Work Experience

Senior AI Systems Engineer August 2025 – Present

Medici Land Governance Washington, DC

• Architected tier-based document intelligence pipeline for land title and property records processing, leveraging multi-modal Vision-Language Models (Claude Sonnet 4, Claude Haiku 4.5, GPT-4o, Gemini 2.0 Flash) to automatically classify document complexity and route to cost-optimized OCR models, reducing processing costs by 60-70% for simple deeds while maintaining 95%+ accuracy on complex handwritten parcels and legal descriptions.

• Built production-scale multi-county title document extraction system integrating cutting-edge OCR technologies

(PaddleOCR, Tesseract, Claude Vision API) with intelligent fallback chains, processing thousands of real estate documents across property deeds, liens, easements, and subdivision maps with 97% text extraction accuracy and automated quality assessment pipelines.

• Developed specialized ML pipeline for historical document analysis processing 300000+ handwritten court dockets from the 1850s, implementing custom column detection algorithms and handwriting enhancement preprocessing that reduced manual review requirements by 40%.

Senior Machine Learning Engineer (Freelance) November 2024 – July 2025 RIOS Intelligent Machines Palo Alto, CA

• Architected production-scale computer vision pipelines using YOLO v8/v9 and PyTorch, achieving 98% accuracy in real-time defect detection for manufacturing robotics, processing 10M+ images daily.

• Designed advanced MLOps infrastructure with Kubernetes and Metaflow, reducing model deployment time by 70% and enabling continuous integration for ML workflows across edge devices.

• Implemented GPU-optimized data loaders with sequence-aware batching, improving training throughput by 40% while maintaining temporal consistency for time-series robotics data. Senior Machine Learning Engineer May 2023 – April 2025 Unstructured IO San Francisco, CA

• Spearheaded comprehensive benchmark study of 10+ Vision-Language Models (Claude 3.5, OpenAI GPT-4o/3.5, Gemini Pro), improving table structure recognition by 15% and boosting image-based text extraction by 20% through model selection optimization.

• Designed and deployed scalable multi-agent orchestration system using LangChain, AutoGen, and Pydantic AI, enabling collaborative LLM reasoning and reducing enterprise document processing time by 45%.

• Built end-to-end RAG pipeline integrating layout detection, PaddleOCR/Tesseract OCR, and PDF parsing, achieving 30% faster throughput across enterprise workflows.

• Fine-tuned transformer-based OCR models using LoRA on 11,000+ domain-specific technical PDFs, improving text accuracy by 12% and reducing missing text cases by 15% across mission-critical enterprise systems. Lead Software Engineer — AI/ML (Freelance) July 2023 – February 2024 Sapient Logic San Diego, CA

• [DOD Classified] Architected OCR system processing over 5,000 field documents daily with 97% accuracy, enabling real-time intelligence extraction from captured images for critical Common Operational Picture (COP) updates.

• [DOD Classified] Engineered multilingual translation system that reduced intelligence processing time by 40% through optimized OCR integration, converting Russian, Arabic, Spanish, and Chinese documents to English with 92% semantic accuracy.

• [DOD Classified] Designed and implemented mission-critical intelligence requirements management system that decreased collection-to-analysis time by 65%, enabling semi-automated validation of intelligence assets. Machine Learning Engineer — MLOps (Freelance) May 2022 – July 2023 RIOS Intelligent Machines Palo Alto, CA

• Architected and deployed AI-powered robotic workcells that increased manufacturing throughput by 25% across enterprise clients, successfully integrating computer vision systems with existing factory automation workflows.

• Developed custom computer vision algorithms that achieved 98% accuracy in part identification and defect detection, enabling real-time quality control for high-volume production environments. Senior Software Architect (Freelance) June 2022 – June 2023 Speechlab AI San Francisco, CA

• Architected high-throughput backend API infrastructure for large language models that scaled to handle 12M+ daily requests, reducing latency by 65% while supporting advanced AI reasoning capabilities across enterprise applications.

• Engineered fault-tolerant multilingual AI system processing content in 8 languages with asynchronous workflows, resulting in 40% user engagement increase and enabling seamless AI-powered localization for global enterprise clients. Senior Software Engineer Technical Lead May 2021 – February 2023 Sapient Logic San Diego, CA

• Architected and implemented HIPAA-compliant Electronic Health Record (EHR) system that reduced patient registration time by 25%, streamlined clinical workflows across 4 healthcare facilities.

• Secured protected health information through custom multi-factor authentication and role-based access controls, ensuring compliance with healthcare data protection regulations. Senior Data Engineer (Freelance) April 2022 – April 2023 Memetica San Francisco, CA

• Designed and implemented end-to-end data transformation pipeline that collected and processed sensitive content from multiple platforms (Gab, Truth Social, 4Chan), incorporating advanced AI-powered text preprocessing logic and real-time data cleaning.

• Developed comprehensive monitoring ecosystem with fault-tolerant architecture combining EFK (Elasticsearch, Fluentd, Kibana) stack with Sentry.io integration, enabling real-time AI alerting and improving incident response time from hours to minutes.

NLP Engineer (Freelance) November 2021 – June 2022 Soul Machines San Francisco, CA

• Engineered advanced conversational AI platform using RASA and Google Dialogflow CX that achieved 98% intent recognition accuracy across 12,000+ daily user interactions, reducing customer support costs by 35%.

• Implemented complex multi-turn dialogues with automated action fulfillment capabilities and continuous learning from user feedback, enhancing conversational experiences and improving user satisfaction. Google Data Engineer (Freelance) May 2021 – May 2022 Collegis Education Chicago, IL

• Architected real-time ETL infrastructure in Google Cloud Platform that processed 250,000+ daily events from external APIs (Phoneburner, Five9, LMS Canvas), reducing data latency by 85%.

• Enabled automated decision workflows that improved data processing speed and accuracy for educational technology platform serving thousands of students by providing timely and precise data insights. Machine Learning Engineer (Freelance) January 2021 – June 2021 Sapient Logic San Diego, CA

• [DOD Classified] Architected and deployed mission-critical security analytics platform using advanced NLP algorithms that mapped Tipping Point’s digital vaccines to the MITRE ATT&CK framework with 94% accuracy.

• [DOD Classified] Reduced false-positive threat identification by 50% while analyzing 10,000+ potential attack vectors to enhance DOD security infrastructure.

Natural Language Processing Engineer (Freelance) April 2019 – May 2021 PlusOne Company Salt Lake City, UT

• Pioneered BERT-based call analytics system that achieved 94% accuracy in real-time sentiment analysis across 50,000+ daily customer interactions, reducing false positives by 40%.

• Optimized multilingual conversation processing through advanced CPU/GPU deployment architecture for enterprise-scale NLP applications.

Software Engineer September 2017 – April 2021

Moody’s Analytics - RMS Silicon Valley, CA

• Collaborated with cross-functional team developing geospatial analytics platform that integrated location intelligence with financial risk assessment, enabling portfolio managers to visualize $200B+ in assets against natural disaster probability zones.

• Reduced risk exposure by 25% for institutional clients through data-driven investment decisions and advanced predictive modeling algorithms.

Projects

Cybersecurity Threat Intelligence Engine: BERT-powered MITRE ATT&CK mapping system processing 1M+ security events daily with 91% threat classification accuracy. Medical Image Analysis Engine: CUDA-optimized deep learning inference system for medical diagnostics with GPU-accelerated signal processing and real-time analysis. Cryptocurrency Trading Signal Engine: LSTM-based Bitcoin prediction system achieving 73% accuracy on 2M+ price points with 50ms latency real-time processing. Urban Environment Analysis: MaskRCNN-based satellite imagery segmentation system processing multi-band geospatial data with automated urban feature detection and classification. Agricultural Drone Vision System: Faster R-CNN ResNet101 model analyzing 3,186+ aerial images for pineapple detection and yield forecasting, enabling precision agriculture for African farmers. Custom Enterprise Data Pipeline: Python-based ETL framework with Docker containerization processing multi-source data (Snowflake, Redshift, SharePoint) for ThoughtSpot analytics integration. Semantic Data Quality Engine: BERT + Sherlock algorithm system achieving 90%+ accuracy in automated column type detection with PySpark integration for enterprise data quality assessment. Veteran Benefits AI Platform: Next.js + Node.js full-stack system integrating VA APIs and HR platforms with intelligent eligibility engine for automated veteran benefits assessment. Military Tactical OCR System: Google ML Kit + Tesseract4Android mobile OCR processing multilingual documents (Russian, Arabic, Chinese, Spanish) for real-time battlefield intelligence. Military Intelligence Management Platform: AI-powered microservices architecture with cross-domain security enabling semi-automated intelligence collection and 65% faster intelligence analyst workflows. Generative AI Marketing Platform: Next.js + tRPC full-stack system with OpenAI and Together.ai integration for automated content generation and marketing optimization workflows. Real-Time Conversational AI Platform: GPT-4o + LangChain backend serving 10K+ daily users with 25% response time reduction through optimized streaming architecture. Education

University of California, Berkeley Berkeley, CA

Bachelor of Arts in Computer Science December 2017 University of California, Berkeley Berkeley, CA

Bachelor of Arts in Cognitive Science December 2017 Certifications

Deep Learning Specialization (DeepLearning.AI and Stanford University), 2024 Machine Learning Specialization (DeepLearning.AI and Stanford University), 2024 AWS Cloud Practitioner Essentials (AWS), 2024

IBM Data Science Specialization (IBM), 2023

Machine Learning Engineering for Production (MLOps) Specialization (DeepLearning.AI), 2024 Google Data Analytics (Google), 2023

Business Intelligence (Google), 2023

Contact this candidate