Machine Learning Operations Engineer – MLOps
Buzz Solutions
full-time
Posted on:
Location Type: Remote
Location: United States
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About the role
- Develop end-to-end backend pipelines for deploying machine learning models.
- Build Docker containers for trained machine learning models.
- Deploy Docker container images on Kubernetes engine.
- Maintain Kubernetes engine and virtual machines on Google Cloud Platform.
- Develop Flask and FastAPI frameworks in Python for deploying models as APIs.
- Deploy the models in production as REST APIs on cloud infrastructure.
- Observe and measure current product performance.
- Review the process and product performance data with the team to develop standard work.
- Document the process, code reviews and workflow to streamline product enhancements.
- Develop end-to-end pipeline for deploying software platform backend infrastructure.
- Build end-to-end methodology for backend modules of the cloud software platform.
- Choose the optimal technology stack for building out the elements of the software platform backend.
- Establish platform features and timelines for product roadmap.
- Integrate SQL database objects with the software platform.
- Integrate machine learning model REST API endpoints with software platform.
- Deploy the platform in production on cloud infrastructure.
- Work with a team of software engineers to enhance performance of the software platform and run continuous unit tests for deployed products.
- Observe and measure current product performance.
- Review the process and product performance data w/ team to develop standard work.
- Document the process, code reviews and workflow to streamline product enhancements.
- Maintain and monitor cloud infrastructure.
- Monitor the logs of customer usage of the products and test for any vulnerabilities.
- Maintain database systems and optimize for 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 enhancements.
Requirements
- Must have a Bachelor’s degree in Computer Science or related field and 4 years of experience, including:
- Designing, implementing, debugging web technologies and server architectures (Java,JavaScript, NodeJS), databases in Cloud Infrastructure and with Python programming language
- Develop applications, API integrations on cloud infrastructures to handle customer data
- Utilizing and maintaining cloud infrastructure and services of Google Cloud Platform
- Employer will accept a Master’s degree and 2 years’ experience in lieu of the Bachelor’s plus 4.
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
PythonFlaskFastAPIDockerKubernetesSQLREST APIsCloud InfrastructureWeb TechnologiesServer Architectures
Soft Skills
Team CollaborationProcess DocumentationPerformance MeasurementStandard Work DevelopmentCode ReviewWorkflow StreamliningProblem SolvingCommunication
Certifications
Bachelor’s Degree in Computer ScienceMaster’s Degree in Computer Science