Open to opportunities

Haven Intezar

@havenintezar

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Senior Machine Learning Engineer specializing in MLOps, scalable pipelines, and production AI systems.

United States

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What I'm looking for

I am seeking senior MLOps/ML engineering roles where I can build scalable, production ML systems, improve model reliability, and mentor teams in data-driven product development.

I am a Senior Machine Learning Engineer with 12+ years building production-ready ML systems across NLP, computer vision, and recommendation engines. I specialize in bridging research and engineering to move models from experimentation into reliable, monitored production services.

My work focuses on scalable pipelines and modern MLOps practices — designing training and deployment workflows with tools like SageMaker, Airflow, Kubeflow, Docker, and Kubernetes, and implementing monitoring and drift detection with Prometheus and ELK.

I have led development of transformer-based NLP models, real-time recommendation engines using Spark Streaming and Kafka, and reproducible CI/CD-driven model serving frameworks. I prioritize transparency, maintainability, and measurable business impact in every solution I deliver.

Experience

Work history, roles, and key accomplishments

Current

Senior Machine Learning Engineer

Current

Closinglock

Jan 2022 - Present (3 years 8 months)

Built production ML pipelines with SageMaker and Airflow, deployed transformer-based NLP models for classification and sentiment, and architected a real-time recommendation engine using Spark Streaming and Kafka while introducing model monitoring and drift detection.

Sagemaker Airflow Transformers Kafka Prometheus MLOps Docker Kubernetes

Machine Learning Engineer

Data Bricks

Dec 2017 - Dec 2021 (4 years)

Delivered demand forecasting models (XGBoost, Prophet) integrated via APIs, built TensorFlow computer vision pipelines for defect detection, and created a low-latency gRPC/Kubernetes model serving framework while automating hyperparameter tuning with Optuna.

XGBoost Prophet TensorFlow gRPC Kubernetes Optuna CI CD Spark APIs

Applied ML Engineer

RealMassive

Aug 2015 - Nov 2017 (2 years 3 months)

Implemented topic modeling and word embedding pipelines for large-scale text analysis, prototyped collaborative filtering recommendation systems, and created Spark pipelines to prepare high-volume training datasets while deploying reproducible CI/CD ML workflows.

Topic modeling Embeddings Collaborative Filtering Apache Spark CI CD Python

Data Scientist

Status Labs

May 2012 - Jul 2015 (3 years 2 months)

Built credit scoring and fraud detection models using logistic regression and ensemble methods, conducted time-series forecasting for financial trends, and produced compliance-ready interpretability reports for regulators and auditors.

Logistic Regression Fraud Detection Time Series Model Interpretability Statistical Modeling Python