Senior ML/AI Engineer

This Senior ML/AI Engineer role requires extensive experience in machine learning and artificial intelligence, emphasizing advanced algorithm development, model design, and deployment. Candidates should have a strong background in programming languages commonly used in ML/AI such as Python, R, or Java, along with proficiency in ML frameworks and libraries like TensorFlow, PyTorch, scikit-learn, or Keras. Expertise in data preprocessing, feature engineering, and working with large-scale datasets is essential. Experience with cloud platforms (AWS, Azure, or Google Cloud) and containerization tools like Docker and Kubernetes is often expected for scalable model deployment. A senior-level engineer should demonstrate skills in designing end-to-end ML pipelines, optimizing model performance, and applying best practices in version control, testing, and documentation. Familiarity with deep learning architectures, natural language processing, computer vision, or reinforcement learning may be required depending on the specific domain. Strong analytical skills, problem-solving abilities, and the capacity to lead projects or mentor junior engineers are important. While no explicit education level is specified, senior roles typically require at least a bachelor's degree in computer science, data science, engineering, or a related field, with many candidates holding advanced degrees. Overall, the role demands a combination of technical expertise, practical implementation experience, and leadership capabilities to drive AI initiatives effectively.