MLOps Engineer

San Francisco, California

MLOps

Permanent

Our client is a data-driven company helping customers save time and costs with their unique AI platform. They are hiring an MLOps Engineer in San Francisco to help them continue to enhance their customer support through cutting-edge Machine Learning tools and techniques.

Responsibilities

As the MLOps Engineer, you will develop and maintain infrastructure for machine learning development and deployment.
Build REST API and gRPC applications in Python to serve models as APIs.
Design end-to-end pipelines for model inference, backend, and data on cloud platforms.
Work with model registries and MLOps frameworks for seamless model deployment.
Implement monitoring tools to track model performance, detect drift, and ensure stability.
Manage cloud infrastructure, including Kubernetes and virtual machines on GCP.
Optimize cloud infrastructure and database performance while reducing costs.
Define and implement AI-driven platform features and roadmap timelines.
Collaborate with software engineers to enhance performance and ensure continuous testing.

Skillset

Master’s or Bachelor’s degree in Computer Science with a minimum of three years of experience working in Machine Learning.
Strong background in designing, implementing and debugging web technologies and server architectures.
Proficient in Python for coding, testing and development.
Hands-on experience with SQL and NoSQL databases in cloud environments.
Experience developing backend applications, API integrations and data pipelines on cloud platforms.
Familiarity with cloud services and infrastructure on Google Cloud, AWS or Azure.