Back to results
Technology & IT

Machine Learning Engineering Intern (MS/PhD) at Riot Games

Riot Games
On-site · Los Angeles, California Internship Internship Competitive salary Posted 2 days ago International
Apply on company site ↗
Not ready to apply yet?
Free ATS check

Check your CV before you apply

See your score the way hiring software reads it. If it needs work, build a stronger resume in the same place.

About the role

Riot Games makes League of Legends, Teamfight Tactics and VALORANT. As a Machine Learning Engineering Intern you work with engineers, data scientists and game teams on how data and ML can shape player experiences and protect fair play, across the full ML cycle.

Key responsibilities

  • Prepare, clean and explore datasets for ML projects
  • Build features, models and evaluations with guidance
  • Create prototypes, analyses or tools about player experience or cheating
  • Test, document and make experiments reproducible
  • Explain findings to technical and non-technical colleagues

Requirements

  • Graduating in 2028 with an MS or PhD in computer science, ML, AI, statistics, maths or similar
  • Comfortable programming in Python
  • Grasp of ML basics, statistics, data structures and algorithms
  • Experience working with data in Python, SQL or notebooks; GPA 2.5 or higher
  • Available full-time for 12 weeks; authorised to work in the US, no visa sponsorship

Nice to have

  • PyTorch, TensorFlow or scikit-learn
  • Cloud or deployment tools
  • Game projects in Unity or Unreal

Location and schedule

  • Los Angeles, California
  • 12 weeks, full-time, summer 2027
  • Applications close 4 January 2027

Salary and benefits

Paid internship with 401(k), in-game perks and the Play Fund. The posting gives an hourly rate of USD 80.77 for remote interns.

How to apply

Apply on the company's own site.

Riot Games
Listed via Employer Career Pages
View companies

Source: Employer Career Pages · THE BRIEFED never charges candidates.

The Weekly Brief

New roles, in your inbox.

One email a week — the best hand-picked roles, salary insights and career reads. No spam, unsubscribe any time.