Remote
Remote only
Available
Responsibilities:
Leading the analysis of current AI adoption and integration maturity across business lines and defining a structured homologation approach for scalable AI deployment in quality processes.
Identifying and delivering quick wins in the field of preventive quality — translating business challenges into concrete AI/ML solutions with measurable impact.
Designing, developing, and deploying production-grade AI and ML applications that automate quality workflows, enable predictive quality insights, and reduce quality-related incidents.
Leveraging advanced prompt engineering techniques (Zero-shot, Few-shot, Chain-of-Thought) and Large Language Models (LLMs) to build intelligent quality tools that augment human decision-making and automate quality workflows.
Driving the development and execution of the aligned Quality Suite 5.0 AI adoption roadmap, informed by real business line requirements and delivering a minimum of three new AI applications in production within the first year.
Acting as the strategic and technical bridge between the Quality Engineering domain and the Digital execution team — defining data requirements, solution architecture, and AI use case prioritization.
Collaborating closely with Data Engineers, Data Scientists, and AI/ML engineers to ensure AI solutions are robust, secure, scalable, and production ready.
Leading in a project environment — influencing without formal authority, aligning cross-functional teams, and delivering results with pace and precision.
Engaging with internal business line stakeholders across GE Vernova's global organization to understand their quality data needs, gather requirements, and iterate solutions based on real-world feedback.
Contributing to the evolution of the Digital Quality Suite, bringing innovative ideas and a forward-thinking mindset to continuously improve our quality tooling landscape.
Documenting solution designs, model performance, and data definitions clearly to ensure transparency and reproducibility across the team.
Staying current with the latest advancements in AI, ML, and responsible AI practices, proactively proposing new approaches that enhance our quality solutions.
Required:
Bachelor’s degree in data science, computer science, statistics, mathematics, engineering, or a related technical field or equivalent experience
Some relevant experience in AI/ML engineering, data science, or a related technical discipline.
Desired:
Master’s degree in data science, computer science, statistics, mathematics, engineering, or a related technical field.
Advanced AI/ML engineering proficiency — hands-on expertise in development with Python, FastAPI, and prompt engineering techniques (Zero-shot, Few-shot, Chain-of-Thought prompting).
Deep understanding of AI quality and robustness — responsible AI principles, model validation, security, bias mitigation, and production-grade AI reliability.
Basic knowledge of quality management processes and methodologies (e.g., APQP, 8D, FMEA, or similar quality KPI frameworks).
Proven self-driven delivery mindset — track record of independently driving projects from concept to production in a fast-paced, cross-functional enterprise environment.
Structured problem-solving with visionary thinking — ability to break down complex challenges into actionable plans while simultaneously driving a forward-looking AI adoption roadmap.
Strong collaborative mindset — able to define requirements clearly and work effectively with a distributed Digital execution team.
Proactive, intellectually curious, and comfortable operating in a dynamic, evolving environment.
Strong storytelling ability — capable of turning complex analytical findings into compelling narratives for business stakeholders.
Background in the energy, automotive, or large-scale manufacturing industries.
Startup or fast-paced scale-up experience — comfortable with ambiguity, rapid iteration, and delivering high-impact results with lean resources.
Familiarity with enterprise platforms such as SAP, Salesforce, or similar ERP/CRM systems from an AI and data integration perspective.
Experience with AWS cloud services from an AI/ML perspective (e.g., SageMaker, S3, Lambda, Bedrock).
Understanding of Semantic Data Models and data modelling concepts across heterogeneous systems.
Exposure to MLOps principles — model versioning, experiment tracking, deployment basics.
Familiarity with version control systems (e.g., Git) and collaborative development practices.
Experience in international, multicultural team environments and working across time zones.
GE Vernova offers a great work environment, professional development, challenging careers, and competitive compensation. GE Vernova is an Equal Opportunity Employer. Employment decisions are made without regard to race, color, religion, national or ethnic origin, sex, sexual orientation, gender identity or expression, age, disability, protected veteran status or other characteristics protected by law.
GE Vernova will only employ those who are legally authorized to work in the United States for this opening. Any offer of employment is conditioned upon the successful completion of a drug screen (as applicable).
Relocation Assistance Provided: Yes
For candidates applying to a U.S. based position, the pay range for this position is between $93,500.00 and $155,900.00. The Company pays a geographic differential of 110%, 120% or 130% of salary in certain areas. The specific pay offered may be influenced by a variety of factors, including the candidate’s experience, education, and skill set.
Bonus eligibility: discretionary annual bonus.
This posting is expected to remain open for at least seven days after it was posted on June 05, 2026.
Available benefits include medical, dental, vision, and prescription drug coverage; access to Health Coach from GE Vernova, a 24/7 nurse-based resource; and access to the Employee Assistance Program, providing 24/7 confidential assessment, counseling and referral services. Retirement benefits include the GE Vernova Retirement Savings Plan, a tax-advantaged 401(k) savings opportunity with company matching contributions and company retirement contributions, as well as access to Fidelity resources and financial planning consultants. Other benefits include tuition assistance, adoption assistance, paid parental leave, disability benefits, life insurance, 12 paid holidays, and permissive time off.
GE Vernova Inc. or its affiliates (collectively or individually, “GE Vernova”) sponsor certain employee benefit plans or programs GE Vernova reserves the right to terminate, amend, suspend, replace, or modify its benefit plans and programs at any time and for any reason, in its sole discretion. No individual has a vested right to any benefit under a GE Vernova welfare benefit plan or program. This document does not create a contract of employment with any individual.
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