Rolls-Royce

Junior Machine Learning Engineer

Rolls-Royce

Indianapolis, Indiana, United States (Hybrid) · Full Time

Be the first to apply

Experience
1+ yrs
Salary
USD 66,306 – USD 107,747 / year
Openings
1
Posted
3 hours ago
Work mode
Hybrid
Education
Bachelor's degree
Eligibility
Applicants must be U.S. Citizens.
Resume
Required to apply

Where you'll work

Job description

Overview

Join Rolls-Royce as a Junior Machine Learning Engineer based in Indianapolis, IN, working on a hybrid schedule requiring a minimum of three days onsite per week. You'll be part of a diverse team addressing complex challenges in AI, machine learning, and data science to create innovative tools that generate insights on Rolls-Royce products.

About Rolls-Royce

Rolls-Royce is a renowned global brand, recognized for over a century of pioneering work in critical power systems prioritizing safety and reliability. The company has earned a place on Forbes' Top Employers for Engineers 2025, reflecting its dedication to innovation and career growth within a collaborative environment. Rolls-Royce fosters an inclusive workplace where all employees are valued and empowered to excel.

Responsibilities

  • Collaborate with IT and engineering teams to identify and apply digital technology solutions that maximize operational impact and value.
  • Process, clean, and analyze large datasets from engine sensors, test rigs, and fleet operations to support data-driven insights.
  • Develop, train, and validate machine learning models for applications including knowledge search, anomaly investigation, production support, and predictive maintenance.
  • Effectively document workflows and clearly communicate findings to audiences with varying technical expertise.

Candidate Profile

Adherence to fundamental principles such as safety, ethical conduct, simplicity, and making a difference are essential. Candidates must demonstrate these behavioral qualities as part of the assessment.

Minimum Qualifications

  • A Bachelor's degree in Engineering, Chemistry, Computer Science, Information Technology, Mathematics, or Physics; or
  • A Master's degree in the aforementioned disciplines; or
  • A PhD in the aforementioned disciplines.
  • U.S. citizenship is mandatory for eligibility.

Preferred Qualifications

  • At least one year of machine learning experience, including internships.
  • Familiarity or enthusiasm for modern software development techniques and programming languages.
  • Experience or interest in surrogate modeling, Generative AI, or Agentic AI solutions.
  • Strong technical and interpersonal skills such as systems thinking, communication, time management, and teamwork across diverse disciplines.
  • An aptitude for solving problems and collaborating with professionals outside the data science domain, such as mechanical systems engineers and support staff.
  • A commitment to continuous learning and adaptability to evolving goals and opportunities.

Compensation and Benefits

Rolls-Royce offers competitive pay ranging from $66,306 to $107,747 annually along with exceptional benefits. These include bonuses, employee support programs, discounts, health and dental insurance, vision care, disability and life coverage, flexible spending and health savings accounts, a 401(k) plan with company match, employee assistance resources, paid time off, holidays, parental and family care leave, tuition reimbursement, and long-term incentives. Benefit options vary depending on eligibility and employment terms.

Working Conditions

The role is hybrid, supporting flexible work arrangements that blend office presence with remote work. Employees are generally expected onsite three days per week for collaboration and key activities. Relocation support is available. Fully remote work is restricted to employees residing outside of Idaho, Nebraska, Nevada, Vermont, and Wyoming.

Additional Details

  • Global Grade: 8
  • Closing Date: August 8, 2026
  • Location: Indianapolis, IN

Work styles they’re looking for

Communication Adaptability Time Management Problem Solving Teamwork Technical Communication Systems Thinking

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