Applied AI Engineer

The Applied AI Engineer will apply artificial intelligence to improve decision-making and engineering productivity within Amcor’s global Flexibles R&D organization. This role focuses on building scalable, responsible AI capabilities that support knowledge discovery, intelligent automation, predictive modeling, and decision support.

Key Responsibilities

• Develop and deploy AI-enabled knowledge systems that connect structured and unstructured enterprise data and R&D content, enabling technical information to become accessible and actionable.
• Deliver AI-assisted decision-support capabilities, including material and construction selection and product design validation, to improve the speed, quality, and consistency of technical and business decisions.
• Address business problems using predictive modeling, intelligent automation, knowledge systems, and generative AI solutions, selecting approaches based on value, practicality, and scalability.
• Implement testing, monitoring, and evaluation practices that support reliability, transparency, and alignment with responsible AI principles.
• Evaluate emerging technologies such as retrieval, generative AI, and applied machine learning, and translate them into practical R&D applications that support Amcor’s long-term AI strategy.
• Build and maintain data structures, semantic layers, metadata, and retrieval mechanisms so AI systems can interpret, connect, and use R&D structured and unstructured information effectively.
• Act as a subject-matter expert for R&D systems by encoding domain knowledge, including schema semantics, data relationships, and units, into AI infrastructure such as model providers, data stores, and orchestration and evaluation frameworks.
• Identify and close data gaps that prevent AI capabilities, partnering with data engineering and IT on general ingestion and pipeline work.
• Define information architecture, knowledge-management standards, and governance approaches to keep R&D knowledge machine-interpretable, reusable, and scalable across AI applications.
• Assess security exposure and cost before extending model access to new R&D systems and data, and help define how each capability fits into global R&D processes ahead of broader rollout.
• Partner with business and other R&D functions to make advanced models, recommendations, and insights more accessible, explainable, and actionable for end users.
• Collaborate with R&D engineers to understand how design decisions are made in practice and build solutions that match real workflows rather than demonstrations.
• Support adoption across business groups through stakeholder engagement, change management, and measurement of business impact and sustained usage.
• Work with IT, Information Security, and Legal to enable responsible AI deployment, covering confidential data protection, data residency, and acceptable use, and translate technical concepts into actionable guidance for multiple audiences.

Required Qualifications

• Degree in Computer Science, Data Science, Software Engineering, Engineering, Applied Mathematics, or a related technical discipline; an advanced degree is advantageous.
• 3+ years of industry experience in software engineering, data science, machine learning engineering, or applied AI, including production-running systems.
• Proven experience delivering applied AI solutions, including large language model applications, machine learning systems, intelligent automation, or knowledge-discovery tools, with measurable business value and adoption.
• Working familiarity with core AI application components: retrieval and embeddings, prompt and context design, structured output, tool use, and evaluation. Strength across multiple areas is expected, with emphasis on applying commercially available technologies to business problems rather than developing foundation models.
• Practical judgment regarding model limitations, including hallucination, retrieval failure, and evaluation, along with experience designing systems that fail safely and visibly.
• Understanding of polymer science, film extrusion, or food-packaging interactions is preferred, and genuine interest in learning the domain is required.
• High proficiency in Python and SQL, including data pipelines and transforming unstructured technical content into machine-usable form; Azure experience is preferred.
• Demonstrated ability to deliver cross-functional projects with measurable business impact.
• Ability to travel occasionally (<10%).

Technologies

• Python, SQL, Azure
• Retrieval, embeddings
• Prompt and context design
• Structured output, tool use, evaluation
• Generative AI, large language model applications

Benefits

• Medical, dental, and vision plans.
• Flexible time off, starting at 80 hours paid time per year for full-time salaried employees.
• Company-paid holidays starting at 8 days per year and may vary by location.
• Wellbeing program & Employee Assistance Program.
• Health Savings Account/Flexible Spending Account.
• Life insurance, AD&D, short-term & long-term disability, and voluntary benefits.
• Paid Parental Leave.
• Retirement Savings Plan with company match.
• Tuition Reimbursement (dependent upon approval).
• Discretionary annual bonus program (initial eligibility dependent upon hire date).

Work Expectations

• Guidance by The Amcor Way and demonstration of Amcor values every day.
• Success measures include engaged teams and development within a high-performing Amcor environment.
• Success measures include customers growing and prospering through Amcor’s quality, service, and innovation.
• Success measures include investors benefiting from Amcor’s consistent growth and superior returns.
• Success measures include the environment benefiting from Amcor’s leadership and products.

Location and Employment Authorization

Location: Neenah, WI (onsite).

E-Verify: Amcor verifies the identity and employment authorization of individuals hired for employment in the United States.