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Machine Learning Operations Engineer

Remote

Job Description 

Join Buzz Solutions and be part of a dynamic team that is shaping the future of energy and technology. If you are passionate about delivering exceptional customer support and thrive in a collaborative and innovative environment, we want to hear from you! Apply now to embark on an exciting journey with us.

 

Responsibilities

  • Build and maintain the infrastructure needed to support machine learning development and deployment.
  • Develop REST API and gRPC applications using Python for deploying models as APIs.
  • Build end-to-end pipelines for model inference, backend and data on the cloud software platform.
  • Integrate SQL and NoSQL database systems with the software platform.
  • Work with model registries and MLOPs frameworks to deploy machine learning models
  • Setup tools and metrics to monitor, analyze drift and maintain machine learning models in production.
  • Develop and maintain CI-CD pipelines to deploy ML based backend artifacts.
  • Monitor the logs of customer usage of the products and test for any vulnerabilities.
  • Containerize ML based backend applications and deploy container images on Kubernetes engine.
  • Maintain cloud infrastructure including Kubernetes engine and virtual machines on Google Cloud Platform.
  • Design and deploy cloud infrastructure, database systems and optimize performance and costs.
  • Provide unit and stress testing frameworks for cloud infrastructure services deployed in production environments.
  • Document the process, code reviews and workflow to streamline product development and enhancements.
  • Establish AI based software platform features and timelines for product roadmap.
  • Review the process and product performance data w/ team to develop standard work.
  • Suggestion optimal and current technological stack for building out the elements of the ML-based software platform backend.
  • Work with a team of software engineers to enhance the performance of the software platform and run continuous unit tests for deployed products.

 

Qualifications & Experience

  • The candidate must have a bachelor’s degree in computer science or related field and 5 years of experience, including:
  • Designing, implementing, debugging web technologies and server architectures 
  • Coding, testing and developing using Python
  • Experience in SQL and NO SQL databases in Cloud Infrastructure 
  • Experience in developing backend applications, API integrations, data pipelines on cloud infrastructures to handle customer data
  • Utilizing and maintaining cloud infrastructure and services of using Google Cloud/AWS/Azure Cloud
  • Employer will accept a master’s degree and 3 years’ experience in lieu of the Bachelor’s plus 4.

 

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