Machine Learning Engineer

Working Pattern: Full-time Working location: Indianapolis, IN (Hybrid Schedule/3 days onsite minimum) We’re looking for a Machine Learning Engineer to join our growing team. In this role, you will tackle exciting challenges in AI/ML, software development, and Data Science. You’ll be part of a multi-disciplinary team, working together to tackle technical challenges in a stimulating and collaborative environment. In this role, your focus will be on building and deploying tools to deliver insights on Rolls‑Royce products. Job Description Job Title: Machine Learning Engineer Working Pattern: Full-time Working location: Indianapolis, IN (Hybrid Schedule/3 days onsite minimum) We’re looking for a Machine Learning Engineer to join our growing team. In this role, you will tackle exciting challenges in AI/ML, software development, and Data Science. You’ll be part of a multi-disciplinary team, working together to tackle technical challenges in a stimulating and collaborative environment. In this role, your focus will be on building and deploying tools to deliver insights on Rolls‑Royce products. Why Rolls‑Royce? Rolls‑Royce is one of the most enduring and iconic brands in the world and has been at the forefront of innovation for over a century. We design, build and service systems that provide critical power to customers where safety and reliability are paramount. We are proud to be a force for progress, powering, protecting and connecting people everywhere. We want to ensure that the excellence and ingenuity that has shaped our history continues into our future and we need people like you to come and join us on this journey. Rolls‑Royce has been recognized as the top employer in the Engineering & Manufacturing category on the prestigious Forbes Top Employers for Engineers list for 2025. This ranking highlights our commitment to innovation, employee development, and fostering a collaborative environment where engineers can thrive. Be part of a team that sets the industry standard and drives groundbreaking solutions. At Rolls‑Royce, we are committed to creating a workplace where all employees feel respected, supported, and empowered to do their best work. We foster a welcoming and innovative work environment that invests in you, giving you access to an incredible breadth and depth of opportunities where you can grow your career and make a difference. Rolls‑Royce is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to any protected characteristics. What You Will Be Doing Work with IT, and Rolls‑Royce Fleet 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. Who We’re Looking For At Rolls‑Royce we put safety first, do the right thing, keep it simple and make a difference. These principles form the behaviours that guide us and are an essential component of our assessment process. They are the fundamental qualities that we seek for all roles. Basic Requirements Bachelor’s degree in Engineering, Chemistry, Computer Science, Information Technology, Mathematics, Data Science, Physics with 2+ years of machine learning experience; OR Masters degree in Engineering, Chemistry, Computer Science, Information Technology, Mathematics, Data Science, Physics, OR PhD in Engineering, Chemistry, Computer Science,, Information Technology, Mathematics, Data Science or Physics. In order to be eligible for consideration, you must be a U.S. Citizen Preferred Requirements 3+ years of machine learning experience Experience in accelerating product design and delivering impactful digital products Experience with modern software development methodologies and coding languages Experience developing solutions in surrogate modelling, Generative AI, or Agentic AI Excellent technical and soft skills including systems thinking aptitude, communications, time management, business acumen, and collaboration across multi-disciplinary teams. Strong problem-solving instincts and the ability to work across disciplines with people who are not data or A.I. specialists but engineer and support mechanical systems. Experience with mentoring and educating other members of the team. Actively learn, develop, apply, and share recently gained knowledge and skills in this face-paced and dynamic discipline. What We Offer We offer excellent development opportunities, a competitive salary, and exceptional benefits. These include bonus, employee support assistance and employee discounts. Your needs are as unique as you are. Hybrid working is a way in which our people can balance their time between the office, home, or another remote location. It’s a locally managed and flexed informal discretionary arrangement. As a minimum we’re all expected to attend the workplace for collaboration and other specific reasons, on average three days per week. For fully remote roles, employees can live in any state except Idaho, Nebraska, Nevada, Vermont, and Wyoming. Relocation assistance is available for this position. Grade Level: GG10 Closing date: 8/8/2026 Job Category: Mechanical Systems Job Posting Date: 04 Aug 2026; 00:08 Pay Range: $98,566 - $160,169-Annually Location: Indianapolis, IN Benefits Base pay and a discretionary bonus plan Health Dental Vision Disability Life and accidental death & dismemberment insurance Flexible spending account Health savings account 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 Long-term incentive plan Option availability depending on eligibility factors such as date of hire, employment type, and the applicability of collective bargaining agreements. #J-18808-Ljbffr