Machine Learning Infrastructure Architect

7 days ago


Houston, Texas, United States Experis Full time
Job Title: Cloud Platform Engineering Lead

The estimated salary for this role in Houston, TX is $145,000 - $175,000 per year.

Job Description:

We are seeking an experienced Cloud Platform Engineering Lead to join our team. As a key member of our organization, you will be responsible for designing, developing, and maintaining the infrastructure for our machine learning applications.

Your primary focus will be on developing automated build and deployment processes to enable continuous delivery of software releases. You will work closely with data scientists, data engineers, data analysts, software engineers, IT specialists, and stakeholders to accelerate the deployment of AI applications via CI/CD pipelines and maintain the SLAs of those applications at the centralized platform.

You will also be responsible for designing, developing, and maintaining infrastructure using infrastructure as code tools such as Terraform, Ansible, CloudFormation, etc. Additionally, you will templatize existing Databricks CLI codes to manage Databricks platform as code for AIML data pipelines (batch processing, batch streaming, and streaming) and model serving endpoints.

Key Responsibilities:

  • Develop automated build and deployment processes to enable continuous delivery of software releases.
  • Collaborate with cross-functional teams to ensure that applications are highly available and scalable.
  • Design, develop, and maintain infrastructure using infrastructure as code tools.
  • Templatize existing Databricks CLI codes to manage Databricks platform as code.
  • Enhance the existing DevOps practices to improve the overall AIML application development lifecycle.
  • Establish and maintain best practices for cloud security, compliance, and cost optimization.

Requirements:

  • Bachelor's Degree in Computer Science, Computer Engineering, Information Technology, Software Engineering, or equivalent technical discipline.
  • 10+ years of experience in software engineering with a strong background in DevOps and Infrastructure as Code, supporting Machine Learning and Data Science workloads preferred.
  • Expertise on code versioning tools, such as GitLab, GitHub, Azure DevOps, Bitbucket, etc., GitHub preferred.
  • Experience deploying Machine Learning solutions on cloud platforms (e.g., AWS, Azure, or GCP). Databricks and AWS preferred.
  • Proficient with GitHub actions to automate testing and deployment of data and ML workloads from CI/CD provider to Databricks.
  • Strong knowledge of infrastructure automation tools such as Terraform, Ansible, CloudFormation, etc.
  • Experience with data processing frameworks/tools/platforms such as Databricks, Apache Spark, Kafka, Flink, AWS cloud services for batch processing, batch streaming, and streaming.
  • Experience containerizing analytical models using Docker and Kubernetes or other container orchestration platforms.
  • Technical expertise across all deployment models on public cloud, private cloud, and on-premises infrastructure.
  • Experience in event-driven, microservice architectures for enterprise-level platform development.
  • Expertise in Linux and knowledge of networking and security concepts.
  • Effective communication skills and a sense of ownership and drive.
  • Capable of coaching/mentoring individuals and teams.


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