AI Full Stack Engineer

Amcor

AI Full Stack Engineer developing AI-powered applications, collaborating with teams to enhance data solutions at Amcor. Engaging in model development, full stack & cloud deployment.

Posted 5/5/2026full-timeDeerfield • Illinois • 🇺🇸 United StatesJuniorMid-Level💰 $85,600 - $107,000 per yearWebsite

Tech Stack

Tools & technologies

AWSAzureCloudDjangoDockerFlaskGoogle Cloud PlatformGraphQLJavaJavaScriptKubernetesMicroservicesNode.jsNoSQLPostgresPySparkPythonPyTorchScikit-LearnSQLTableauTensorflow

About the role

Key responsibilities & impact

Design and develop machine learning models and algorithms tailored to specific business needs.
Design and implement production‑ready RAG systems that connect LLMs to enterprise data sources (data lake, Microsoft Fabric, SAP, MES, document repositories);
Build AI agents that orchestrate multi‑step workflows
Work closely with data scientists, software engineers, and cross-functional teams to integrate models into production systems.
Analyze large and complex datasets to extract actionable insights and improve model performance.
Tune and enhance model performance and accuracy through iterative testing and validation.
Maintain thorough documentation of AI/ML models, experiments, and processes to ensure reproducibility and knowledge sharing.
Stay abreast of the latest advancements in AI and ML technologies to apply innovative solutions in projects.
Establish and maintain working relationships with Amcor business stakeholders.
Engage enterprise decision makers and stakeholders to facilitate group decisions and outcomes.
Design and build end-to-end AI-powered applications encompassing frontend user interfaces, backend APIs, and integration layers that surface AI/ML model outputs to end users.
Develop and maintain RESTful and/or GraphQL APIs and backend microservices that connect AI/ML models to enterprise data sources and front-end applications.
Design, implement, and optimize relational and NoSQL database schemas to support AI application data needs, including vector databases for embedding storage and retrieval.
Deploy and manage full stack applications on cloud platforms (Azure/AWS/GCP); implement CI/CD pipelines, containerization (Docker/Kubernetes), and infrastructure-as-code practices to ensure reliable, scalable delivery of AI solutions.

Requirements

What you’ll need

Bachelor’s in computer science, Machine Learning, or a related field
2 - 4 years’ experience as an AI/ML Engineer or in a similar role, with a strong understanding of machine learning algorithms and principles
Experienced in Large Language Models, Transformers, CNN, Scikit-learn, NLP libraries, Embedding Models, Vector Databases, AI Agents, and Agentic orchestrations.
Familiarity with deep learning frameworks such as TensorFlow or PyTorch, Kerasand proficiency in programming languages like Python, PySpark, R, or Java.
Experience with data visualization tools (Power BI and Tableau)
Proficiency in modern frontend web technologies and frameworks (e.g. component-based UI libraries, HTML5, CSS3)
Experience designing and building RESTful and/or GraphQL APIs using Python-based frameworks (e.g. FastAPI, Flask, Django) or Node.js;
Understanding of microservices architecture and API security best practices.
Hands-on experience with relational databases (e.g. SQL Server, PostgreSQL) and NoSQL/vector databases; ability to design schemas, write optimized queries, and manage data pipelines that feed AI applications.
Familiarity with containerization (Docker, Kubernetes), CI/CD tooling, and infrastructure-as-code on major cloud platforms (Azure, AWS, or GCP) to deploy and operate full stack AI solutions reliably at scale.

Benefits

Comp & perks

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)

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

machine learninglarge language modelstransformersconvolutional neural networksscikit-learnnatural language processingembedding modelsvector databasesRESTful APIsGraphQL APIs

Soft Skills

collaborationcommunicationrelationship buildingdecision facilitationdocumentationproblem-solvinganalytical thinkinginnovation

Certifications

Bachelor’s in computer scienceMachine Learning certification