Machine Learning Operations Engineer at Buzz Solutions

Job description

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. *Buzz Solutions does not provide sponsorship for work authorizations in the United States at this time*

Requirements

Must-haves

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

Nice-to-haves

None flagged.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

machine learningrestapipythonsqlmlkubernetesaiawsazure

Platform: greenhouse
Effort: quick