Artificial Intelligence Graduate- US

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.

AVEVA requires all successful applicants to undergo and pass a drug screen before they start employment. All drug screens are in accordance with federal laws and regulations.