Staff Platform Engineer

About the role

The Center for Translational Data Science (CTDS) at the University of Chicago is a research center dedicated to developing translational data science to address scientific and medical challenges. We operate open-source software platforms designed for translational data science and provide support for researchers to utilize these platforms.

Responsibilities

• Provide production support, production monitoring, CI/CD design & implementation, security automation, and AI/ML infrastructure management across open-source software platforms.
• Deploy, monitor, and maintain machine learning models for inference, optimize model and hardware performance, troubleshoot AI/ML solutions, and integrate them within broader application environments.
• Design and implement top priority technical tasks, ensuring timely delivery and meeting required quality standards.
• Lead and mentor interns and less experienced team members, providing technical guidance and fostering a collaborative environment.
• Participate in the hiring process, offering constructive feedback during interviews.
• Advocate for optimal technical solutions, both internally and externally, through negotiation and presentation of options.
• Collaborate with team members to define guidelines and best practices, ensuring accountability for deliverables and outcomes.
• Manage workload to meet project milestones and deadlines, breaking down complex tasks into manageable components and prioritizing them appropriately.

Requirements

Minimum requirements include a college or university degree in a related field and 5-7 years of work experience as a system or DevOps engineer. Advanced degree in computer science, mathematics, statistics, engineering, or a relevant quantitative field is preferred.

Qualifications

• Advanced degree in computer science, mathematics, statistics, engineering, or a relevant quantitative field.
• 6+ years professional experience as a system or DevOps engineer.
• Hands-on scripting experience (Bash, Python, or other dynamic language).
• Unix/Linux programming or system administration experience.
• Experience with OpenStack and AWS cloud technologies.
• Experience with configuration management utilities (Chef, Puppet, Ansible).
• Experience with F5 or other load balancing technologies (Nginx, AWS ELB/ALB, etc.).
• Experience with source control and build systems (SVN, Git, Jenkins, etc.).
• Experience with container-based deployment (Docker, Kubernetes).
• Experience with log aggregation tools (ELK stack, Splunk).
• Experience with security frameworks (FISMA, NIST, FIPS).
• Experience with cloud platforms (AWS, GCP, Openstack), CI/CD, and Agile methodologies.
• Experience leading DevOps initiatives and process improvement.
• Experience with deploying, maintaining, and monitoring AI/ML models and infrastructure.