Junior Machine Learning Engineering

Rolls-Royce is seeking a Junior Machine Learning Engineer to join its growing team. The role focuses on applying AI, machine learning, software development, and data science to build and deploy tools that deliver insights on Rolls-Royce products. Responsibilities include analyzing engineering datasets, developing machine learning models, collaborating with engineering teams, and presenting findings to technical and non-technical audiences.

What you'll do:

• Work with IT, and Rolls-Royce engineering teams address key opportunities for application of digital technologies providing optimal impact and value
• Understand, clean, and analyze large datasets from engine sensors, test rigs, and fleet operations
• Build, train, and validate machine learning models for tasks such as searching engineering knowledge, anomaly research, production support, and predictive maintenance
• Document your work clearly and present findings to both technical and non-technical audiences

What they're looking for:

• Working towards a bachelor's, master's, or PhD in Engineering, Chemistry, Computer Science, Information Technology, Mathematics, Physics, and or related degree and graduation date December 2026 or May 2027
• A strong passion for the future of technology
• A willingness to work flexibly and travel between locations: in most cases, you'll be able to meet the requirements in the location you are recruited to, however, we may need you to be flexible and travel between sites during or for your internship
• Open-minded, curious, and agile approach to work and career development
• Minimum GPA:3.0
• To be considered, you must also be a U.S. Citizen
• Graduating between December 2026 and June 2027

Benefits:

• A discretionary bonus plan
• Eligible employees may have the opportunity to enroll in health, dental, vision, disability, life and accidental death & dismemberment insurance
• A flexible spending account
• A health savings account
• A 401(k) retirement savings plan with a company match
• Employee Assistance Program
• Paid Time Off
• Certain paid holidays
• Paid parental and family care leave
• Tuition reimbursement