Machine Learning and Data Science Engineering Intern

AI in this role

Machine learning and data science intern applying predictive models to data center telemetry and AI infrastructure operations.

python

ai-evaluationai-researchmachine-learningdata-sciencedata-analysisstatistical-modeling

About the job

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.

The team and culture

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.

What we’re looking for

Current enrollment at junior or senior undergraduate level, or in a master's program, in data science, AI, machine learning, computer science, statistics or a related field
Foundational knowledge of machine learning, statistics and data analysis through coursework, research, projects or practical experience
Programming experience in Python, with familiarity using common data-analysis libraries
Experience preparing, exploring, analyzing and visualizing datasets
Understanding of supervised machine learning concepts, including regression, classification, model training and model evaluation
Clear communication, a methodical approach to problem-solving and willingness to seek guidance when needed

While we have outlined a set of requirements, we value transferable skills and diverse experiences.

Benefits

Flexible working: Balance your work and personal life with greater flexibility
Comprehensive healthcare: Medical, dental and vision coverage to help keep you and your family healthy
Phantom equity: Share in Graphcore’s success
Tax-advantaged healthcare savings: Flexible Spending Accounts (FSAs) and Health Savings Accounts (HSAs) to help you make the most of your healthcare spending
Peace of mind protection: Disability and life insurance to provide financial security when you need it most
Retirement planning support: A 401(k) plan to help you invest in your future
Commuter benefits: Help cover the cost of your daily commute
Wellbeing resources: Access to wellness services that support your physical and mental health
Employee Assistance Program (EAP): Confidential advice and support for you and your family across a range of personal, financial and wellbeing matters

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.

Join the Team at Graphcore

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.

How we rate this

Machine Learning and Data Science Engineering Intern at Graphcore rates 85 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.

Prepare for this job

A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.

Skills and AI tools this role asks for

AI EvaluationAI ResearchMachine LearningData ScienceData AnalysisStatistical ModelingPython

Questions you could be asked

How do you decide that one model's output is better than another's for a given task?
Tell me about a research question you investigated. What did you find?
Tell me about a project where machine learning was part of your work. What did you do?
Tell me about a project where data science was part of your work. What did you do?
Tell me about a project where data analysis was part of your work. What did you do?

Adapt your resume

List these exact terms on your resume: AI Evaluation, AI Research, Machine Learning, Data Science, and Data Analysis. An applicant tracking system matches the wording, not the idea.
Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
Lead with what you built, trained or shipped — this role is judged on the AI system itself, not the tools around it.

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