GE Vernova AI Engineer

GE Vernova • Greenville, NC

7d • $73,600 - $110,400 • Onsite

About The Position

As an entry-level AI Engineer, you will help design, build, integrate, and operate AI-enabled applications for engineering and industrial use cases. You will work across software, machine learning, and data interfaces, partnering with Data Scientists, Data Engineers, software teams, and domain experts. This role is designed for a recent graduate who enjoys building working systems, learning new technologies, and turning prototypes into maintainable solutions.

The required work location is Greenville, South Carolina. Relocation assistance is available. The role requires access to U.S. export-controlled information; where applicable, final offers are contingent on obtaining U.S. Government authorization for that access. Unrestricted work authorization in the United States is required, and sponsorship will not be provided now or in the future.

The stated U.S. pay range is $73,600 to $110,400, with geographic differentials in certain areas. The specific offer may depend on experience, education, and skills. The position is eligible for a discretionary annual bonus. The posting was expected to remain open for at least seven days after its posting date of October 27, 2026.

GE Vernova describes its work environment as offering professional development, challenging careers, and competitive compensation. Employment decisions are made without regard to legally protected characteristics. Employment offers are conditioned on successful completion of a drug screen, as applicable.

Requirements

• Recent graduate with a Bachelor's or Master's degree in Computer Science or a STEM major (Science, Technology, Engineering, and Math).
• 0–1 year of related experience in STEM.
• Programming experience in Python and familiarity with at least one additional language or software-development ecosystem.
• Foundational understanding of machine learning, data structures, algorithms, APIs, and software testing.
• Experience using Git and building a working software or AI project through coursework, research, internships, co-ops, hackathons, open-source work, or an independent portfolio.
• Ability to diagnose technical problems, learn unfamiliar tools, and communicate tradeoffs clearly.
• Demonstrated teamwork, ownership, curiosity, and attention to quality.
• Unrestricted work authorization in the United States; sponsorship is not available now or in the future.
• Ability to obtain U.S. Government authorization to access U.S. export-controlled information, if applicable.

Nice To Haves

• Exposure to PyTorch, TensorFlow, scikit-learn, Hugging Face, LangChain, Semantic Kernel, or comparable AI frameworks.
• Exposure to retrieval-augmented generation, AI agents, vector search, model evaluation, or prompt engineering.
• Familiarity with SQL, REST APIs, cloud services, Docker, Kubernetes, CI/CD, MLflow, or observability tools.
• Experience with distributed or GPU computing, optimization, surrogate models, simulation workflows, or scientific computing.
• Interest in renewable energy, industrial software, physical systems, manufacturing, or engineering applications.

Responsibilities

• Build and test AI-enabled applications, APIs, model services, automation workflows, and user-facing tools under the guidance of experienced engineers.
• Integrate machine-learning or generative-AI capabilities with approved data sources, engineering tools, and enterprise platforms.
• Translate Data Scientist prototypes into modular, readable, and testable software components.
• Implement evaluation, validation, logging, monitoring, and feedback mechanisms to make solution quality and reliability visible.
• Use Git, code reviews, automated testing, documentation, and continuous integration practices to support maintainable delivery.
• Package and deploy workloads using approved cloud, container, and orchestration patterns; troubleshoot issues across development and test environments.
• Improve model or workflow performance through experimentation, prompt or retrieval design, optimization, and careful measurement.
• Collaborate with end users and subject-matter experts to make AI tools useful in day-to-day engineering workflows.
• Follow cybersecurity, privacy, intellectual property, software quality, and Responsible AI requirements throughout the lifecycle.
• Share reusable components, lessons learned, and technical documentation with the broader AI engineering community.

Benefits

• Medical, dental, vision, and prescription drug coverage.
• Access to Health Coach from GE Vernova, a 24/7 nurse-based resource.
• Access to the Employee Assistance Program, including 24/7 confidential assessment, counseling, and referral services.
• GE Vernova Retirement Savings Plan, including a tax-advantaged 401(k) savings opportunity with company matching and company retirement contributions.
• Access to Fidelity resources and financial planning consultants.
• Tuition assistance.
• Adoption assistance.
• Paid parental leave.
• Disability benefits.
• Life insurance.
• 12 paid holidays.
• Permissive time off.
• Relocation assistance.
• Discretionary annual bonus eligibility.

What This Job Offers

• Job Type: Full-time
• Career Level: Entry Level