Applied AI Engineer: AI for R&D Knowledge & Automation

Amcor Limited; Neenah (WI); On-site; USD 120,000 - 180,000; Full time

Benefits offered by this job

Medical benefits

Dental benefits

Vision benefits

Paid time off

Holidays

Job summary

Amcor Limited seeks an Applied AI Engineer at the Neenah Innovation Center to accelerate AI-driven R&D innovation. You will apply AI to improve decision making, productivity, and governance for global Flexibles R&D, shaping Amcor’s AI strategy with data‑driven insights and scalable solutions.

You will collaborate with IT, Security, and business stakeholders to deliver responsible, measurable impact while advancing knowledge systems, data pipelines, and embeddings throughout the organization.

Qualifications

• Degree in Computer Science, Data Science, Software Engineering, Engineering, or Applied Mathematics.
• 3+ years in software engineering, data science, ML engineering, or applied AI with production systems.
• Experience building applied AI solutions with measurable business impact.
• Proficiency in Python and SQL; Azure experience preferred.

Responsibilities

• Develop and deploy AI-enabled knowledge systems across R&D data.
• Provide AI-assisted decision support to improve speed and quality of decisions.
• Solve problems using predictive modeling, automation, and knowledge systems.
• Establish testing, monitoring, and responsible AI practices.
• Translate emerging AI tech into practical applications for R&D strategy.

Skills

Python

SQL

Applied AI

Cross-functional delivery

Education

Degree in CS / Data Science / Software Eng / Applied Math

Tools

Azure

Job description

Amcor Limited seeks an Applied AI Engineer at the Neenah Innovation Center to accelerate AI-driven R&D innovation. You will apply AI to improve decision making, productivity, and governance for global Flexibles R&D, shaping Amcor’s AI strategy with data‑driven insights and scalable solutions.

You will collaborate with IT, Security, and business stakeholders to deliver responsible, measurable impact while advancing knowledge systems, data pipelines, and embeddings throughout the organization.