R&D Senior Packaging Engineer - Machine Learning

$79,800 - $133,450/Yr

PepsiCo - Valhalla, NY

Full-time - Mid Level

Valhalla, NY

Beverage and Tobacco Product Manufacturing

About the position

The R&D Senior Packaging Engineer - Machine Learning at PepsiCo is responsible for advancing packaging engineering capabilities through the integration of machine learning, data analytics, and virtual design tools. This role focuses on optimizing packaging performance and quality, driving innovation in packaging technologies, and collaborating with cross-functional teams to enhance consumer experiences and operational efficiency. The engineer will leverage advanced analysis techniques to support the development of sustainable packaging solutions and ensure robust design from creation to disposal.

Responsibilities

• Lead development of advanced analysis capabilities, leveraging FEA, ML techniques, data science and advanced analytics principles to optimize performance of palletized goods under distribution testing.
• Act as a subject matter expert concerning multi-variate data analytics, modeling and simulation and digital twins by continuously researching to stay updated on the latest advancements in AI/ML technologies.
• Develop software solutions for distribution test performance prediction leveraging physical and virtual data and extract meaningful insights that can be used to optimize packaging performance and quality.
• Drive packaging innovation and integrate analytical models into existing distribution systems and associated supply chain for real-time monitoring of palletized goods and decision making.
• Support the development of the overall AI/ML strategy, aligning it with business goals.
• Work with lab team to extract physical test data from smart, instrumented lab tools (accelerometers, GPS sensors, temperature sensors, computer vision tools) to feed data models.
• Maintain open communication and build strong relationships with multiple functions including PepsiCo's R&D, Engineering, Operations and Supply Chain Development Teams.
• Collaborate with executive leadership to understand organizational objectives and translate them into actionable strategic initiatives.
• Protect information and materials provided to third parties by ensuring proper procedures are conducted and parties are contractually obligated to follow PepsiCo's Non-Disclosure Agreements as necessary.

Requirements

• MS or PhD in Packaging, Engineering, Mechanical Engineering, Data Science and Analytics with proven academic experience in developing and implementing FEA simulations, AI/ML and/or digital twin solutions in related consumer goods field.
• MS candidates with 2+ years of industry experience in hands-on distribution testing under standard protocols similar to methods by ISTA.
• PhD graduates with experience in hands-on distribution testing under standard protocols similar to methods by ISTA.
• Demonstrated expertise on application of data science and analytics principles in industrial applications, to verify performance and manufacturability, and drive form/fit/function optimization.
• Solid experience with applying data science and analytics software and tools, advanced engineering, and simulation preferred.
• Strong leadership qualities, verbal and written communication skills, and technical analysis and problem-solving skills are required.

Nice-to-haves

• Experience with finite element analysis software: Abaqus, LS-Dyna, ANSYS, Fluent, MSC -Nastran, SW Simulation.
• Experience with CAD software: SolidWorks, Catia, Creo/ProE, Fusion360 is a plus.
• Project management skills.
• Strong communication and presentation skills.
• Teamwork & collaboration.
• Motivated & results driven.
• Innovative thinking.
• Ability to work in an ambiguous and dynamic work environment.

Benefits

• Medical, Dental, Vision, Disability, Health, and Dependent Care Reimbursement Accounts
• Employee Assistance Program (EAP)
• Insurance (Accident, Group Legal, Life)
• Defined Contribution Retirement Plan
• Paid time off including paid parental leave, vacation, sick, and bereavement
• Bonus based on performance and eligibility; target payout is 8% of annual salary paid out annually.