Staff Platform Engineer

About the role

The Center for Translational Data Science (CTDS) at the University of Chicago is a research center dedicated to advancing translational data science. We develop and operate open-source software platforms for translational data science, providing researchers with the necessary data and tools to drive impactful discoveries.

Responsibilities

• Provide production support, production monitoring, CI/CD design & implementation, security automation, and AI/ML infrastructure management across open-source software platforms.
• Triage, research, communicate, and address production incidents.
• Wrangle disparate system monitoring assets and develop common analytics for optimization.
• Define benchmarks and confidence intervals, and forecast to proactively mitigate production incidents.
• Deploy, monitor, and maintain machine learning models for inference.
• Optimize model and hardware performance, troubleshoot AI/ML solutions, and integrate them within the broader application environment.
• Lead DevOps initiatives and process improvement.
• Deploy, maintain, and monitor AI/ML models and infrastructure.

Requirements

• Minimum 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.
• 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).
• Experience with source control and build systems (SVN, Git, Jenkins).
• 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.

Qualifications

• Collaborate with team members and help define guidelines and best practices.
• Take and provide constructive and helpful input and feedback on technical issues.
• Negotiate complex decisions, present options, and advocate for optimal technical solutions.
• Considered a Subject Matter Expert in most DevOps technology and solutions.
• Break down complex tasks into smaller ones, estimate effort, prioritize, and ensure completion.
• Work collaboratively and ensure accountability for deliverables and outcomes.
• Prioritize and manage workload to meet project milestones and deadlines.

Skills

• Technical knowledge of existing and emerging technologies, including public cloud offerings from Amazon Web Services, Microsoft Azure, and Google Cloud.
• Ability to lead DevOps initiatives and process improvement.
• Experience with deploying, maintaining, and monitoring AI/ML models and infrastructure.

Benefits

• Healthcare coverage.
• Pension plan.
• Flexible time off.