Machine Learning Engineer - Recommendation

Requirements:

• 5+ years of professional experience in end-to-end development of large-scale machine learning systems in production.
• Strong experience developing and delivering end-to-end machine learning solutions, from experimentation to model deployment, including backend engineering and MLOps in large-scale production systems.
• Experience using common machine learning frameworks such as TensorFlow and PyTorch and libraries such as scikit-learn, NumPy, and pandas.
• Deep understanding of machine learning and software engineering fundamentals.
• Basic knowledge of monitoring systems, logging, and common production operations.
• Strong communication skills to collaborate effectively with multiple teams and stakeholders.

Nice To Have:

• Experience developing recommender systems using large-scale datasets.
• Basic knowledge of enterprise search systems and related stacks such as ELK.
• Functional development and bug-fixing skills to improve system performance and reliability.
• Experience with Docker and Kubernetes.
• Experience with cloud platforms such as AWS, GCP, or Microsoft Azure.
• Experience in microservice development and operations using Docker and Kubernetes.
• Experience utilizing deep learning models or LLMs in production.
• Publications in top-tier peer-reviewed conferences or journals.

Skills

AWS, Docker, GCP, Kubernetes, ML, MLOps, Machine Learning, PyTorch, Scikit-learn, TensorFlow