Open to opportunities

Naeem Khan

@naeemkhan1

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Senior Machine Learning Engineer driving scalable AI solutions, model deployment, and MLOps excellence.

United States

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What I'm looking for

I seek roles where I can lead ML platform development and MLOps adoption, deliver scalable, production AI, mentor teams, and align AI with business impact.

I am a Senior Machine Learning Engineer with deep experience building and deploying production-grade AI systems across industries. I specialize in Python frameworks, TensorFlow, PyTorch, and modern MLOps practices.

At AgileNinja I led an 8-person ML team to architect a scalable ML platform that halved model processing time and implemented MLOps (Docker, Kubernetes, CI/CD), reducing time-to-production by 40% while delivering a company-wide fraud detection system that cut fraudulent transactions by 35%.

Previously, I managed five production ML models at HorizonIT, improved sales-forecast accuracy by 30%, and optimized training pipelines to reduce training time by 50%. Earlier work as a software engineer involved large-scale data preprocessing and building TensorFlow/PyTorch models achieving strong predictive performance.

I mentor engineers, collaborate with product and executive stakeholders to align AI initiatives with business objectives, and contribute to internal AI/ML knowledge sharing. I am committed to continuous learning and delivering robust, scalable AI solutions.

Experience

Work history, roles, and key accomplishments

Current

Sr. Machine Learning Engineer

Current

AgileNinja

Feb 2022 - Present (4 years 4 months)

Led a team of 8 ML engineers to architect and deploy a scalable ML platform, reducing model processing time by 50% and cutting time-to-production by 40% through MLOps practices.

Python Docker Kubernetes MLOps TensorFlow MLFlow CI CD

Machine Learning Engineer

HorizonIT

Nov 2019 - Feb 2022 (2 years 3 months)

Managed a portfolio of 5 production ML models and optimized predictive sales models to improve forecast accuracy by 30%, while reducing training time and improving data processing efficiency by 50%.

Python TensorFlow PyTorch Model Monitoring Data Pipelines Performance Optimization

Software Engineer

Intellirent

Jan 2018 - Nov 2019 (1 year 10 months)

Collected and preprocessed large datasets (~500GB) and developed initial ML models achieving 85% accuracy for churn prediction, improving baseline performance by 15% through hyperparameter tuning.