Artificial Intelligence Graduate- US

AVEVA is a global leader in industrial software. Our cutting-edge solutions are used by thousands of enterprises to deliver the essentials of life – such as energy, infrastructure, chemicals and minerals – safely, efficiently and more sustainably.

We’re the first software business in the world to have our sustainability targets validated by the SBTi, and we’ve been recognized for the transparency and ambition of our commitment to diversity, equity, and inclusion. We’ve also recently been named as one of the world’s most innovative companies.

If you’re a curious and collaborative person who wants to make a big impact through technology, then we want to hear from you! Find out more at .

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Job Title: AI/ ML New Graduate

Work Type: Hybrid (3 days a week in office)

Work Authorization: This application is intended for candidates that are eligible for full-time work authorization in the United States upon completing their education.

• Please be prepared to answer the following in your application:Do you now, or will you in the future, require sponsorship for employment visa status (e.g. H-1B, F1, CPT, OPT visa status, etc.) to work legally in the United States?

Office Location: Lake Forest, CA

Artificial Intelligence and Machine Learning at AVEVA

We are looking for passionate graduates to join our R&D team. In this role, you will help develop AI capabilities into our existing suite of products or help build AI-enabling platform services and public APIs that are secure, reliable, and cloud-native. These services will act as foundational building blocks for AI adoption across AVEVA’s product portfolio and partner ecosystem.

You will part of a Scrum team to build innovative, standards-compliant, secure and production-grade AI capabilities, with a builder mindset - rapid prototyping and continuous improvement with agility of a start-up.

Key Responsibilities:

• Collaborate with cross-functional teams to design, develop, and deploy machine learning models and AI solutions for real-world problems.
• Assist in data collection, preprocessing, and exploratory data analysis to ensure high-quality datasets for model training and evaluation.
• Implement, test, and optimize machine learning algorithms using relevant libraries and frameworks such as TensorFlow, PyTorch, or scikit-learn.
• Contribute to the development and refinement of AI pipelines, including data ingestion, feature engineering, model selection, and validation.
• Conduct literature reviews to stay updated on the latest trends, techniques, and developments in the field of AI and machine learning.
• Document technical processes, experiments, and results to facilitate knowledge sharing and reproducibility within the team.
• Participate in code reviews, brainstorming sessions, and team meetings to foster a collaborative and innovative working environment.
• Present findings, analyses, and results effectively to both technical and non-technical stakeholders.

Desired Skills and Knowledge in AI/ML:

• Solid understanding of foundational AI and machine learning concepts, including supervised and unsupervised learning, classification, regression, clustering, and model evaluation.
• Familiarity with algorithms such as linear regression, logistic regression, decision trees, support vector machines, neural networks, and ensemble methods.
• Proficiency in programming languages commonly used in AI/ML, such as Python or R, along with experience using relevant libraries (e.g., NumPy, pandas, scikit-learn, TensorFlow, PyTorch). Knowledge of C# and .Net would be an advantage.
• Knowledge of data preprocessing techniques, feature selection, and dimensionality reduction.
• Basic experience with data visualization tools and techniques to communicate insights from data.
• Understanding of deep learning architectures particularly transformer models, and foundational knowledge of Large Language Models (LLMs) and generative AI concepts.
• Familiarity with prompt engineering techniques for interacting with generative AI models and basic knowledge of RAG (Retrieval Augmented Generation) architectures.
• Awareness of emerging AI interoperability standards, such as Model Context Protocol (MCP) and Agent2Agent (A2A), and their role in building interconnected AI systems.
• Ability to work with version control tools such as Git, and familiarity with collaborative development practices.
• Strong problem-solving skills, analytical thinking, and attention to detail.
• Excellent written and verbal communication skills.
• Prior internships, coursework projects, or research experience in AI/ML is a strong plus.