About the role
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.