Machine Learning Engineer Resume Example

“Machine learning engineer with 5 years building end-to-end ML systems from prototype to production. Expert in PyTorch, TensorFlow, and MLOps tooling with experience deploying models serving millions of predictions daily across recommendation, search, and fraud detection domains.”

• Deployed production ML models serving 10M+ predictions daily. P99 latency stays under 50ms using TorchServe on Kubernetes
• Built the MLOps pipeline with MLflow for experiment tracking, automated retraining, and model versioning across 15 models
• Developed a fraud detection model that runs in real-time - 95% precision at 80% recall. Prevents about $8M in fraud annually
• Cut recommendation model inference time by 70% through quantization, ONNX conversion, and request batching
• Designed the feature store on Feast. Serves 500+ features to 10 ML models and eliminated 80% of duplicate feature engineering
• Responsible for model monitoring in production - tracking prediction drift, data quality, and latency metrics with automated alerts
• Worked with the data engineering team to build training data pipelines that pull from 5 different source systems
• Wrote model training scripts in PyTorch and set up distributed training on multi-GPU instances for our largest models
• Participated in weekly model review meetings where we discuss model performance, A/B test results, and upcoming experiments

Include these keywords in your resume to pass Applicant Tracking Systems.

• Google Professional Machine Learning Engineer
• AWS Certified Machine Learning - Specialty