Ml Operations Engineer Job in Uniphore

Job Responsibilities:

• Design, Develop and maintain the Data science platform and programming framework to enable consistent, reliable, and consumable data science services
• Test, deploy, maintain, and improve ML models/infrastructure and software that uses these models
• Collaborate with the data engineers and data scientists on feature development to containerise and build out the deployment pipelines for new modules
• Identify and evaluate new patterns and technologies to improve the performance, maintainability, and elegance of our machine learning systems
• Create and work with docker files, images, and containers to test and deploys data science

Requirements:

• 3+ years experience working with ML teams to deliver AI models to production
• Experience working with deep learning frameworks (such as TensorFlow, Keras, Torch, Caffe, Theano)
• Working experience with any of MLOps platforms like KubeFlow/MLFlow/Dataiku/H20/Seldon/SageMaker.
• Solid experience with python tools for data-science.
• Ability to develop and implement sample ML/DL algorithms
• Experience with container technologies like Kubernetes/Docker/AKS/EKS/OpenShift and ecosystem of cloud native solutions.
• Prior experience developing features for Data Science validation and testing to track model performance, API response time, and test coverage metrics
• Design software architecture and data flow for scalable machine learning development work
• Understanding of REST APIs for invoking, integrating, and orchestrating.
• Excellent oral and written communication skills.
• Comfortable working with remote teams