Data Science Intern - Summer 2027
Intern
We sent a six-digit code to . Enter it below — or use the link in the same email.
Or click the link in the same email — either works.
Enter the email address on your account and we'll send you a link to set a new password.
Remembered it? Sign In
Analyze telemetry from data center facilities to help engineers spot patterns and make reliability decisions. You'll clean datasets, build predictive models, create visualizations and share findings with technical colleagues. This internship requires current undergraduate or master's enrollment in data science, machine learning, computer science or statistics, with foundational knowledge of machine learning and statistics. Programming experience in Python and familiarity with data-analysis libraries are essential. Based in Austin.
Written from this posting by Neural Jobs AI. The full description is below.
Turn your machine learning coursework into insight that helps AI infrastructure run more reliably.
As a Machine Learning and Data Science Engineer Intern, you will analyze telemetry from data center facilities and engineering infrastructure. You will apply data science and machine learning methods to real operational data.
Your work will help engineers spot patterns, understand anomalies and make better-informed decisions. You will learn how infrastructure data connects to reliability, performance and day-to-day operations.
You will clean and explore datasets, build reproducible analyses and evaluate predictive models. You will also create visualizations, document assumptions and share findings with technical colleagues.
This internship gives you practical experience with real-world infrastructure data, supported by engineers who value curiosity and clear thinking.
You will work with the Facilities Reliability Engineering team in Austin. The team supports infrastructure used to develop and test the next generation of AI systems.
Work happens through clear operational questions, shared data exploration, prototype analysis and practical review with engineers. Decisions are shaped by evidence, operational knowledge, reproducible results and honest discussion of uncertainty.
You will own defined tasks with guidance, feedback and room to ask questions. As an intern, you will build confidence by turning data into insight engineers can use.
While we have outlined a set of requirements, we value transferable skills and diverse experiences.
We welcome people from all backgrounds and experiences and are committed to building an inclusive environment where everyone can do their best work.
We’re an equal opportunity employer and recognize that everyone brings different strengths and perspectives. If you need any accommodations during the interview process, just let us know - we're happy to support you.
Graphcore is one of the world’s leading innovators in Artificial Intelligence compute. It is developing hardware, software and systems infrastructure that will unlock the next generation of AI breakthroughs and power the widespread adoption of AI solutions across every industry.
As part of the SoftBank Group, Graphcore is a member of an elite family of companies responsible for some of the world’s most transformative technologies. Together, they share a bold vision: to enable Artificial Super Intelligence and ensure its benefits are accessible to everyone.
Graphcore’s teams are drawn from diverse backgrounds and bring a broad range of skills and perspectives. A melting pot of AI research specialists, silicon designers, software engineers and systems architects, Graphcore brings together deep expertise to solve complex problems and deliver meaningful progress in AI compute.
Ready to spend your internship applying machine learning to real infrastructure data?
Apply now to join Graphcore as a Machine Learning and Data Science Engineer Intern.
Here is what this employer asked for. Sign in and we will fill in your half.
Graphcore designs the Intelligence Processing Unit, a processor architected specifically for machine-intelligence workloads, together with the Poplar software stack that compiles models onto it.
Founded in Bristol in 2016 and acquired by SoftBank in 2024, the company builds silicon and systems for AI training and inference.
Already have an account? Sign in
Continue without an account and apply on the Graphcore website
Search by role, company, or anything a posting mentions.