Machine Learning Engineer

Job Summary:

• A Machine Learning Engineer designs, builds, and deploys machine learning models and systems that enable data-driven automation and intelligence.
• They work closely with data scientists and software engineers to turn prototypes into scalable, production-ready AI solutions.

Responsibilities:

• Design and develop machine learning models and algorithms for predictive and analytical tasks
• Build and optimize data pipelines for model training and deployment
• Collaborate with data scientists to transform research models into production applications
• Monitor and improve model performance, accuracy, and efficiency
• Implement MLOps best practices for automation, deployment, and maintenance
• Stay updated with the latest AI/ML frameworks, techniques, and tools

Required Skills & Qualifications:

• Bachelor’s or Master’s degree in Computer Science, Data Science, or related field
• Strong programming skills in Python (and familiarity with R, Java, or C++)
• Experience with ML frameworks: TensorFlow, PyTorch, Scikit-learn
• Proficiency in data preprocessing, model evaluation, and feature engineering
• Knowledge of cloud platforms (AWS, Azure, GCP) and containerization tools (Docker, Kubernetes)
• Understanding of statistics, linear algebra, and probability

Common Tools & Technologies:

• Languages: Python, R, SQL
• Libraries: TensorFlow, PyTorch, Scikit-learn, Pandas
• Tools: Jupyter, MLflow, Airflow
• Cloud: AWS SageMaker, GCP Vertex AI, Azure ML