Senior ML Engineer

The Senior ML Engineer role requires extensive experience in machine learning engineering, typically involving several years of hands-on work developing, deploying, and maintaining machine learning models in production environments. Candidates should possess deep expertise in core machine learning algorithms, data preprocessing, feature engineering, and model evaluation techniques. Proficiency in programming languages such as Python and familiarity with ML frameworks and libraries like TensorFlow, PyTorch, or scikit-learn is essential. Experience with data engineering tools and platforms, including SQL, distributed computing, and cloud services (e.g., AWS, GCP, or Azure), is highly valuable. The role demands strong skills in designing scalable ML pipelines, optimizing model performance, and ensuring robustness and reliability of ML systems. Senior-level engineers are expected to contribute to architectural decisions, mentor junior team members, and collaborate closely with cross-functional teams including data scientists, software engineers, and product managers. Familiarity with MLOps practices, version control, containerization (Docker), and CI/CD pipelines for ML workflows is also important. While formal education details are not specified, senior roles typically require a solid foundation in computer science, statistics, or related fields. Overall, the position calls for a seasoned professional capable of leading complex ML projects end-to-end and driving innovation within the organization.