Description:

The MLOps Engineer will be part of a product team focused on enhancing a self-service platform for AI solutions within a Fortune 500 pharmaceutical company.
The role involves administering and optimizing Databricks within AWS environments, expanding features and capabilities, and implementing new releases of Databricks features.
Responsibilities include managing Databricks environments for high availability, performance, and security.
The engineer will implement and maintain Databricks on serverless architectures, ensuring seamless CI/CD pipelines and integration with AWS services.
The position requires developing best practices for machine learning lifecycle management and collaborating with data scientists and developers to automate AI model development.
The role also involves leveraging AWS services and maintaining familiarity with Azure for cross-compatibility and optimal platform performance.
Additionally, the engineer will manage Kubernetes namespace-level operations within AWS EKS, including application deployment and environment configuration.

Requirements:

Candidates must have 3+ years of experience in a similar role with proven expertise in Databricks and AWS, and preferably some exposure to Azure.
A strong background in MLOps, DevOps, and cloud technologies is required, ideally within a similar industry.
Knowledge of AWS AI Services is essential for this position.

The position offers the opportunity to work with leading enterprises and innovative startups on cutting-edge projects.
Employees will be part of a transformative initiative that drives innovation and business growth in the pharmaceutical industry.
The role provides a chance to collaborate with a product team focused on deploying AI solutions across the company, enhancing technological capabilities.