Performance Engineering Intern

Job Description

Software Engineer Intern – Data Infrastructure and Tools | PlusAI

The Tone:
This is an internship at PlusAI, a company pioneering AI-based virtual driver software for factory-built autonomous trucks, headquartered in Silicon Valley. This role is crucial for the team, as it involves designing and implementing automated systems that monitor, visualize, and alert on the performance of these complex autonomous systems. You will play a key part in transitioning manual performance checks into a robust, data-driven pipeline, directly contributing to the reliability and efficiency of future autonomy.

The TL;DR
• Role: Internship
• Location: In-person, Santa Clara, CA
• Pay: $19–$65 hourly
• Mission: To transition the team from manual performance checks to a fully automated data pipeline, leveraging both production and release candidate CI data.
• Tech Stack: Python, Git, JavaScript, Jenkins, GitHub Actions, GitLab CI, Buildkite, Grafana, Prometheus, Datadog, ELK stack, APIs

What You’ll Actually Do
• Monitoring Systems: Design and implement continuous automated monitoring pipelines for crucial system performance characteristics, including node start times, system-critical code sections, and end-to-end latency metrics.
• CI/CD Integration: Integrate performance tracking into release branch Continuous Integration (CI) environments and build on-demand testing capabilities for GitHub/GitLab Pull Requests.
• Automate Alerting: Develop mechanisms to automatically detect, flag, and escalate performance outliers and regressions in real-time.
• Data Visualization & Trend Analysis: Create systems or dashboards to track and visualize overall performance trends based on specific variables such as workload and geographic location.
• Bridge the Gap: Transition the team from manual, “human-eye” performance checks to a fully automated data pipeline that makes the best use of both production and release candidate CI data.

The Must-Haves
• Background: Student with a solid understanding of backend software development principles, data structures, system architecture, and an analytical mindset for identifying bottlenecks and working with data infrastructure.
• Experience: Strong, hands-on programming experience with Python for backend development and automation, combined with a foundational understanding of Continuous Integration workflows, version control (Git), and automated testing principles.
• Skills: Python proficiency, backend software development, data structures, system architecture, CI/CD knowledge, Git, automated testing principles, problem-solving, and data infrastructure analysis.
• Bonus: Basic knowledge or hands-on experience with JavaScript, prior exposure to industry-standard CI/CD platforms (e.g., Jenkins, GitHub Actions, GitLab CI), experience with performance monitoring and visualization tools (e.g., Grafana, Prometheus), an understanding of distributed systems or edge computing environments, and experience working with APIs, large datasets, or managing data pipelines.