ML Operations Engineer
Bengaluru or Chennai
Uniphore
Uniphore, a world leader in Conversational AI, offers distinct solutions in Conversational Automation, Self-service, Interaction Analytics, Agent Security and Co-pilot Solutions, to enrich the Customer Service ExperienceAt Uniphore, we believe companies that best understand and act on those conversations will win. We have built the most comprehensive and powerful conversational automation platform that combines conversational AI, workflow automation, and RPA (Robotic Process Automation) with a business user-friendly-UX (User Experience) in a single integrated platform to transform and democratize customer experiences across industries.
The Data Science Group is seeking a MLOps Engineer who can build and maintain MLOps pipelines to support development, experimentation, continuous integration, continuous delivery, verification/validation, and monitoring of AI/ML models. Prior experience working on deployment of NLP and ASR models is a huge plus.
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
Tags: APIs Caffe Conversational AI Deep Learning Docker Keras Kubernetes Machine Learning MLFlow ML models MLOps NLP Pipelines Python SageMaker TensorFlow Testing Theano UX
Perks/benefits: Career development
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