Senior ML | Data Engineer | Python Developer
Results-driven Machine Learning and Data Engineer with strong expertise in Python development, specializing in building scalable data pipelines, deploying ML models, and optimizing analytics platforms. Skilled in designing and maintaining ETL workflows, architecting high-performance data solutions, and leveraging SQL, Spark, and distributed systems to process large-scale datasets. Experienced in training, tuning, and deploying models in production with frameworks like PyTorch, TensorFlow, and Scikit-learn. Adept at cloud-native solutions on AWS, GCP, and Azure, including containerized services with Docker and Kubernetes. Known for writing clean, production-ready code, implementing CI/CD, and collaborating with cross-functional teams to translate complex business requirements into data-driven solutions.
Key strengths include:
Python development for ML pipelines, data engineering, and API services.
End-to-end ML lifecycle: data preprocessing, feature engineering, model training, evaluation, and deployment.
Expertise with databases (Postgres, MySQL, MongoDB) and modern warehouses (BigQuery, Snowflake, Redshift).
Data engineering with Spark, Airflow, Kafka, dbt, and cloud data platforms.
Strong background in scalability, performance optimization, and automation of workflows.
