Description

Lead the automation and scaling of machine learning application lifecycles through advanced DevOps and infrastructure practices.

Responsibilities

• Develop automated build and deployment processes to enable continuous delivery for software releases and AIML applications.
• Design, develop, and maintain infrastructure using Infrastructure as Code (IaC) tools.
• Templatize Databricks CLI codes to manage the platform as code for batch, batch streaming, and streaming data pipelines and model serving endpoints.
• Collaborate with data scientists, engineers, and IT specialists to accelerate AI application deployment and maintain SLAs.
• Enhance DevOps practices to improve the overall AIML application development lifecycle and ensure high availability and scalability.

Required Skills

• 10+ years of software engineering experience with a focus on DevOps and IaC, or 5+ years with a Master's degree.
• Experience deploying machine learning solutions on AWS, Azure, or GCP.
• Proficiency with GitHub Actions to automate testing and deployment from CI/CD providers to Databricks.
• Strong knowledge of infrastructure automation tools such as Terraform, Ansible, or CloudFormation.
• Experience with data processing frameworks including Databricks, Apache Spark, Kafka, Flink, or AWS batch/streaming services.
• Expertise in containerizing analytical models using Docker and Kubernetes.
• Proficiency in Python and R.
• Deep understanding of code versioning and branch-level repository management using Gitlab, GitHub, Azure DevOps, or Bitbucket.
• Technical expertise across public cloud, private cloud, and on-premises deployment models.

Preferred Skills

• Direct experience with AWS and Databricks.
• Advanced expertise using GitHub for version control.

Key Skills

Education

Bachelor's degree in Computer Science