Offer summary

Qualifications:

3+ years of experience in MLOps or a similar role., Proven expertise in Databricks and AWS, with some exposure to Azure., Strong background in DevOps and cloud technologies., Knowledge of AWS AI Services is desirable..

Key responsibilities:

Manage and optimize Databricks environments for high availability and performance.

Implement and maintain CI/CD pipelines and integration with AWS services.

Develop best practices for machine learning lifecycle management and collaborate with data scientists.

Manage Kubernetes namespace-level operations within AWS EKS for application deployment.

Job description

About us:

At Xenon7, we work with leading enterprises and innovative startups on exciting, cutting-edge projects that leverage the latest technologies across various domains of IT including Data, Web, Infrastructure, AI, and many others. Our expertise in IT solutions development and on-demand resources allows us to partner with clients on transformative initiatives, driving innovation and business growth. Whether it's empowering global organizations or collaborating with trailblazing startups, we are committed to delivering advanced, impactful solutions that meet today’s most complex challenges.

About the Client:

Join one of the Fortune 500 leaders in the pharmaceutical industry that is looking innovate and expand our technological capabilities. The person would join a product team working on their self-service company-wide platform that enables all the teams and business units to deploy their AI solutions, making them accessible across the entire company.

Position Summary:

As an MLOps Engineer, you will play a crucial role in the product team. You will focus on administering and optimizing Databricks within AWS environments, expanding features and capabilities on Databricks, assessing new releases of Databricks features, implementing them to the platform, and generally supporting the business teams with their requests for the platform.

Key Responsibilities:

Databricks Administration: Manage and optimize Databricks environments, ensuring high availability, performance, and security.
DevOps Engineering: Implement and maintain Databricks on serverless architectures, ensuring seamless CI/CD pipelines and robust integration with AWS services.
MLOps Implementation: Develop and enforce best practices for machine learning lifecycle management using Databricks. Collaborate with data scientists and developers to automate and streamline our AI model development.
AWS and Azure Integration: Leverage a broad range of AWS services and maintain familiarity with Azure to ensure cross-compatibility and optimal performance of our platforms.
Namespace Administration in EKS: Manage Kubernetes namespace-level operations within AWS EKS, including application deployment and environment configuration.

Requirements

3+ years in a similar role with proven expertise in Databricks, AWS, and preferably some exposure to Azure.
Strong background in MLOps, DevOps, and cloud (desirable if in a similar industry)
Knowledge of AWS AI Services

Required profile