Your Name
Machine Learning Engineer
City, India · +91 98XXX XXXXX · your.name@email.com · linkedin.com/in/yourname · github.com/yourname
Professional Summary
Machine Learning Engineer with 6 years of backend experience in fintech and 2 years building production ML. Shipped an XGBoost fraud model serving 1.5M daily predictions through FastAPI and Docker, with MLflow tracking and drift monitoring. Combines strong software engineering with Feature Engineering, model evaluation and MLOps.
Skills
- Languages: Python, SQL, Java
- Machine Learning: scikit-learn, XGBoost, LightGBM, PyTorch, Feature Engineering, Model Evaluation, A/B Testing
- MLOps & Serving: Model Deployment, FastAPI, Docker, MLflow, Model Monitoring, CI/CD (GitHub Actions)
- Data & Cloud: PostgreSQL, Spark, AWS (S3, SageMaker, ECS), Airflow
Professional Experience
Senior Software Engineer (ML), Northwind Payments Pvt. Ltd., Bengaluru Apr 2021 to Present
- Built and deployed an XGBoost fraud detection model with 40 engineered features; raised fraud recall from 0.62 to 0.81 at constant precision, saving an estimated ₹3.2 crore a year.
- Served the model through FastAPI and Docker on AWS ECS at 1.5M predictions/day with p95 latency of 38 ms.
- Introduced MLflow experiment tracking and a model registry, cutting time to production for new models from 6 weeks to 10 days.
- Set up Model Monitoring for data drift across 40 features with automated retraining alerts; caught a festival season drift 5 days before it affected approvals.
- Ran an A/B Testing rollout with risk and product teams, confirming a 22% drop in chargebacks with no increase in false declines.
Software Engineer, Fabrikam Logistics, Hyderabad Jul 2018 to Mar 2021
- Developed Java and Python microservices for shipment tracking handling 300K requests/day.
- Built a delivery time Regression model in scikit-learn that reduced late delivery estimates by 18%.
Projects
Product Recommendation Service · PyTorch, FastAPI github.com/yourname/Recsys
- Implemented a two tower recommender in PyTorch on 2M interactions; improved recall@20 by 31% over a popularity baseline.
Education
B.Tech, Computer Science, Your University · 2018
Certifications
- AWS Certified Machine Learning Specialty
- Machine Learning Engineering for Production (MLOps), DeepLearning.AI