Entry Level Data Scientist Machine Learning Jobs in Irvine, CA

AVEVA is creating software trusted by over 90% of leading industrial companies.
Salary Range:
$87,400.00 - $145,800.00
This pay range represents the minimum and maximum compensation that the position offers, and final compensation can vary within the range depending on work location, job experience, skills, and relevant educational attainment and/or training.
Job Title: Artificial Intelligence & Machine Learning Graduate - USA (AI Native)
Office Location: Lake Forest, CA
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?
Position Overview
As an AI and Machine Learning New Graduate at AVEVA, you won't be working in the margins - you'll be building at the core. Embedded within a Scrum-based R&D team with a builder's mindset, you will design and deploy production-grade AI capabilities and cloud-native platform services that serve as the foundational infrastructure for AI adoption across a global industrial software portfolio used by more than 20,000 enterprises worldwide.
The scope spans the full depth of modern AI - from classical machine learning and transformer architectures through Large Language Models, Generative AI, Retrieval-Augmented Generation, prompt engineering, agentic workflows, embeddings, and model evaluation - while pushing into what's next: emerging interoperability standards like Model Context Protocol (MCP) and Agent2Agent (A2A) that are actively defining how the next generation of interconnected AI systems communicate and scale.
At AVEVA, new graduates don't just consume AI tools - they build the APIs and platform services that make them possible. If you're ready to move with startup agility, think at enterprise scale, and contribute real solutions that shape the future of intelligent industrial software, this is where that journey begins.
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:

• A Bachelor's Degree, Master's Degree or PhD in Computer Science; Computer Engineering; Data Science; AI/ML graduating with a GPA of 3.0 or above

• Prior internships, coursework projects, or research experience 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.

• An eagerness to accept and expand upon skills and knowledge based on feedback

USA Benefits include:
Flex work hours, 20 days PTO rising to 25 with service, three paid volunteering days, primary and secondary parental leave, well-being support, medical, dental, vision, and 401K.
It's possible we're hiring for this position in multiple countries, in which case the above benefits apply to the primary location. Specific benefits vary by country, but our packages are similarly comprehensive.
Find out more: aveva.com/en/about/careers/benefits/
Hybrid working
We work in a hybrid way at AVEVA. Most roles are based at a local AVEVA office, with an expectation of being on-site 50% of your working hours to support collaboration and connection. Some positions are fully office-based depending on the nature of the work, and certain roles that support specific customers or markets may be remote. The working arrangement for this position will be confirmed during the hiring process.
Hiring process
Interested? Great! Get started by submitting your cover letter and CV through our application portal. AVEVA is committed to recruiting and retaining people with disabilities. Please let us know in advance if you need reasonable support during your application process.
Find out more: aveva.com/en/about/careers/hiring-process
About AVEVA
AVEVA is a global leader in industrial software with more than 6,500 employees in over 40 countries. 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 are committed to embedding sustainability and inclusion into our operations, our culture, and our core business strategy. Learn more about how we are progressing against our ambitious 2030 targets: sustainability-report.aveva.com/
Find out more: aveva.com/en/about/careers/
AVEVA requires all successful applicants to undergo and pass a drug screening and comprehensive background check before they start employment. Background checks will be conducted in accordance with local laws and may, subject to those laws, include proof of educational attainment, employment history verification, proof of work authorization, criminal records, identity verification, credit check. Certain positions dealing with sensitive and/or third-party personal data may involve additional background check criteria.
AVEVA is an Equal Opportunity Employer. We are committed to being an exemplary employer with an inclusive culture, developing a workplace environment where all our employees are treated with dignity and respect. We value diversity and the expertise that people from different backgrounds bring to our business. AVEVA provides reasonable accommodation to applicants with disabilities where appropriate. If you need reasonable accommodation for any part of the application and hiring process, please notify your recruiter. Determinations on requests for reasonable accommodation will be made on a case-by-case basis.