Razin M. - ML/AI Full Stack Engineer

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Albuquerque, United States

Experience

Apr 2024 - Oct 2025

1 year 7 months

ML/AI Full Stack Engineer

AssistWell

Deployed production CatBoost gradient boosting model for healthcare claim scoring, processing 100K+ claims/day with sub-second latency using singleton caching, optimized feature engineering and Pandas/NumPy pipelines.
Developed PyTorch NLP pipeline with BERT transformers for automated ICD-10 medical code classification, fine-tuned on domain text achieving 90%+ accuracy and CPU-optimized inference.
Deployed YOLOv8 models computer vision using PyTorch and MLflow for table structure detection in reimbursement forms, enabling real-time document inference and bounding box extraction.
Built semantic search system with sentence transformers and ChromaDB, supporting vector-based similarity search and persistent/HTTP-managed collections for medical policy documents.
Architected hybrid fraud detection system combining ML, rule-based and statistical algorithms with Django + Celery async processing, achieving 95%+ precision and PostgreSQL audit trails.
Implemented explainable AI layer using case-based reasoning, retrieving similar cases from Parquet datasets and generating compliance-ready JSON outputs via Django REST Framework.
Engineered large-scale ETL pipeline with Pandas multi-table joins, Pydantic data validation and PostgreSQL transformations handling complex healthcare claim hierarchies.
Implemented distributed Celery/Redis async processing system with ACID transactions, error recovery mechanisms and Flower monitoring dashboard supporting 10K+ concurrent batch workflows.
Established MLOps infrastructure with versioned CatBoost artifacts, multi-tenant deployments, PyTest evaluation frameworks and Azure Blob Storage metrics tracking for continuous model monitoring.
Built Django REST Framework APIs with OpenAPI documentation, JWT/API key auth and Gunicorn WSGI server and CORS configuration serving 1M+ monthly requests at 99.9% uptime.
Architected normalized PostgreSQL schema with 15+ Django ORM models, polymorphic storage, django-simple-history audit logs and 90% query optimization through ORM techniques.
Built enterprise React/TypeScript application using Ant Design, TanStack React Query, styled-components, framer-motion and Vite build system with modular architecture.
Implemented comprehensive testing with Vitest, Cypress E2E, Storybook, MSW mocking, ESLint/Prettier tooling and Sentry monitoring achieving 80%+ coverage.

May 2021 - Mar 2024

2 years 11 months

Generative AI & Backend Engineer

ColomboAI

Engineered and deployed a generative AI API leveraging LLMs and RAG to automate marketing content creation, integrating LangChain, LangGraph and OpenAI models with AWS-based production infrastructure.
Developed and integrated AI pipelines using LangChain and FastAPI to automate audio enhancement workflows, implementing asynchronous background task execution using Celery and AWS Lambda for scalable deployment.
Built and deployed an AI-powered conversational chatbot trained on behavioral recovery literature, containerized with Docker and Kubernetes on GCP, leveraging LlamaIndex-based embeddings and reinforcement learning models to improve personalization and recommendation quality.
Trained and optimized an AI assistant using RLHF and LoRA fine-tuning, improving NLP model accuracy and contextual response quality.
Orchestrated large-scale AI automation workflows on AWS, using Step Functions, Bedrock, DynamoDB, Amplify, and Lambda to support real-time newsletter and media generation powered by multimodal LLMs including OpenAI and Claude.
Built an end-to-end real estate valuation system with Airflow MLFlow and automating retraining and deployment for continuous predictions.
Developed a natural language data-querying app with FastAPI and React, enabling Text-to-SQL generation and analytics through fine-tuned LLM prompts.

Feb 2020 - Apr 2021

1 year 3 months

Software Engineer

Kustomer

Built BERT and Bi-LSTM models for text classification, entity recognition, and chatbots, integrated with React/Next.js dashboards.
Designed and deployed production AI models via Flask backend for content generation, ensuring robust API services, real-time inference, and fully tested integration with frontend applications.
Developed interactive React/Next.js dashboards and web applications to visualize AI predictions and analytics, integrating seamlessly with Flask backend services and content generation pipelines.
Engineered AWS-based ML pipelines with Docker, Lambda, and SageMaker, enabling automated inference and retraining workflows.

Jul 2016 - Jan 2020

3 years 7 months

Junior Software Developer

Poweron Technology Services

Built a real-time recommendation engine using collaborative filtering and scikit-learn, driving personalized user experiences.
Developed embedding model for sentences splitting instead of word tokenizer using PyTorch, spaCy and Apache Kafka, improving operational efficiency.
Implemented a computer vision application with OpenCV and TensorFlow, automating quality control processes in manufacturing.
Created an automated machine learning pipeline with MLflow and scikit-learn, accelerating model development and deployment.
Engineered a predictive maintenance system using time-series forecasting and Prophet, reducing downtime and maintenance costs.
Conducted data visualization and exploratory data analysis (EDA) with Matplotlib and Seaborn, uncovering critical business insights.
Collaborated with cross-functional teams to integrate ML models into existing systems, ensuring seamless operation and value delivery.

Summary

Senior ML/AI Full-Stack Engineer with 9+ years designing and deploying production-grade machine learning systems and enterprise applications. Expert in deep learning (PyTorch, TensorFlow), predictive analytics (CatBoost, XGBoost), and full-stack development (React/TypeScript, Python/Django, Node.js). Specialized in NLP, computer vision, and classical ML—building scalable AI solutions with Kafka, Celery, ChromaDB/Pinecone, AWS, Azure, MLflow, Docker, and Kubernetes.

Proven leader driving ML best practices, mentoring teams, and delivering measurable impact: $5M+ annual savings, 75% process automation, and 90%+ model accuracy across healthcare, fintech, and e-commerce domains.

Languages

English

Native

Education

Oct 2012 - Jun 2016

Montana State University

Bachelor's Degree · Computer Science · United States

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Experience

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Summary

Languages

Education

Montana State University

Bachelor's Degree · Computer Science · United States

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