Machine Learning Operations Engineer

This is a fully remote position, open to applicants in United States.

📋 Description

• Construct and uphold the infrastructure necessary for the development and deployment of machine learning applications.

• Create REST API and gRPC applications utilizing Python to deploy models as APIs.

• Develop comprehensive pipelines for model inference, backend operations, and data on the cloud software platform.

• Integrate SQL and NoSQL database systems into the software platform.

• Collaborate with model registries and MLOps frameworks to implement machine learning models.

• Establish tools and metrics to monitor, analyze drift, and maintain machine learning models in a production environment.

• Create and sustain CI/CD pipelines for deploying ML-based backend artifacts.

• Oversee customer product-usage logs and conduct vulnerability testing.

• Containerize ML-based backend applications and deploy container images on Kubernetes Engine.

• Manage Google Cloud infrastructure, including Kubernetes Engine and virtual machines.

• Design and implement cloud infrastructure and database systems while optimizing for performance and cost-efficiency.

• Provide frameworks for unit and stress testing of cloud infrastructure services in production.

• Document processes, conduct code reviews, and streamline workflows to enhance product development.

• Define features and timelines for the AI-based software platform as part of the product roadmap.

• Analyze process and product performance data with the team to establish standard work practices.

• Recommend optimal and contemporary technology stacks for the ML-based software platform backend.

• Collaborate with software engineers to improve platform performance and execute continuous unit tests for deployed products.

⛳️ Requirements

• A bachelor's degree in computer science or a related field along with 5 years of experience is required.

• Proficiency in designing, implementing, and debugging web technologies and server architectures.

• Experience in coding, testing, and development using Python.

• Familiarity with SQL and NoSQL databases within cloud infrastructure.

• Background in developing backend applications, API integrations, and data pipelines on cloud infrastructures to manage customer data.

• Experience in utilizing and maintaining services within Google Cloud, AWS, or Azure cloud infrastructure.

• A master's degree and 3 years of experience may be accepted in place of a bachelor's degree plus 4 years of experience.

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

🏝️ Benefits

• Competitive salary and performance bonuses.

• Comprehensive health insurance plans.

• Opportunities for professional development and continuing education.

• Flexible work hours and remote work options.

• Engaging work environment with a focus on innovation.