✨ About The Role
- The Senior MLOps Engineer will design, build, and maintain end-to-end machine learning pipelines, including data ingestion, model training, validation, deployment, and monitoring.
- This role involves implementing Continuous Integration/Continuous Deployment (CI/CD) processes to automate the testing and deployment of machine learning models in production environments.
- The engineer will be responsible for building and owning the production infrastructure necessary for serving ML models, ensuring high availability and scalability.
- Collaboration with data scientists, data engineers, and software engineers is key to ensure seamless integration of ML models into production systems.
- The role includes monitoring and optimizing model performance, addressing issues such as data drift and model degradation.
- The engineer will also automate data and model management, developing solutions for version control and experiment tracking.
- Conducting root cause analysis and troubleshooting issues in ML pipelines is a critical responsibility.
- Comprehensive documentation of ML pipelines and operational workflows will be required to ensure knowledge sharing and continuity.
âš¡ Requirements
- The ideal candidate should have a bachelor's degree in computer science, engineering, or a related field.
- A minimum of 5 years of experience in MLOps or ML engineering is required for this role.
- Candidates should possess hands-on expertise in building and maintaining ML pipelines and scalable ML production infrastructure.
- Strong knowledge of CI/CD practices for ML models is essential for success in this position.
- Familiarity with DevOps principles and tools, as well as experience with frameworks like TensorFlow or PyTorch, is highly desirable.
- Proficiency in programming languages such as Python and Java (or Scala) is necessary.
- Excellent communication skills and the ability to work collaboratively in a team environment are crucial.
- A passion for leveraging cutting-edge ML and AI solutions to revolutionize the way people purchase essential goods is important.