AI/ML Implementation Engineer

This is a fully remote position, open to applicants in United States.

📋 Description

• Overseeing the evaluation of current AI implementation and integration maturity across various business sectors while establishing a systematic homologation strategy for scalable AI integration in quality processes.

• Recognizing and executing immediate opportunities in preventive quality — converting business challenges into tangible AI/ML solutions that yield measurable results.

• Creating, developing, and launching production-ready AI and ML applications that automate quality workflows, provide predictive quality insights, and minimize quality-related incidents.

• Utilizing advanced prompt engineering methods (Zero-shot, Few-shot, Chain-of-Thought) and Large Language Models (LLMs) to create intelligent quality tools that enhance human decision-making and streamline quality workflows.

• Leading the formulation and implementation of the aligned Quality Suite 5.0 AI adoption roadmap, guided by genuine business line requirements and achieving a minimum of three new AI applications in production within the first year.

• Serving as the strategic and technical liaison between the Quality Engineering domain and the Digital execution team — outlining data requirements, solution architecture, and prioritizing AI use cases.

• Collaborating closely with Data Engineers, Data Scientists, and AI/ML engineers to ensure that AI solutions are robust, secure, scalable, and ready for production.

• Taking the lead in a project environment — influencing without formal authority, coordinating cross-functional teams, and achieving results with speed and precision.

• Engaging with internal business line stakeholders across GE Vernova's global organization to comprehend their quality data needs, gather requirements, and refine solutions based on real-world feedback.

• Contributing to the advancement of the Digital Quality Suite, delivering innovative ideas and a forward-thinking perspective to continually enhance our quality tooling landscape.

• Documenting solution designs, model performance, and data definitions meticulously to ensure transparency and reproducibility within the team.

• Keeping abreast of the latest developments in AI, ML, and responsible AI practices, proactively suggesting new approaches that improve our quality solutions.

⛳️ Requirements

• Bachelor’s degree in data science, computer science, statistics, mathematics, engineering, or a related technical field.

• 3+ years of pertinent experience in AI/ML engineering, data science, or a related technical area.

• Master’s degree in data science, computer science, statistics, mathematics, engineering, or a related technical field (preferred).

• Advanced proficiency in AI/ML engineering — hands-on experience in development using Python, FastAPI, and prompt engineering techniques (Zero-shot, Few-shot, Chain-of-Thought prompting).

• Comprehensive understanding of AI quality and robustness — including responsible AI principles, model validation, security, bias mitigation, and production-grade AI reliability.

• Basic understanding of quality management processes and methodologies (e.g., APQP, 8D, FMEA, or similar quality KPI frameworks).

• Proven self-motivated delivery mindset — a history of independently guiding projects from concept to production in a dynamic, cross-functional enterprise setting.

• Structured problem-solving abilities with visionary thinking — the capability to decompose complex challenges into actionable plans while simultaneously advancing a forward-looking AI adoption roadmap.

• Strong collaborative mindset — able to clearly define requirements and work effectively with a distributed Digital execution team.

• Proactive, intellectually curious, and adept at functioning in a dynamic, evolving environment.

• Strong storytelling skills — capable of transforming complex analytical findings into compelling narratives for business stakeholders.

• Background in the energy, automotive, or large-scale manufacturing industries (preferred).

• Experience in startup or fast-paced scale-up environments — comfortable with ambiguity, rapid iteration, and delivering high-impact results with limited 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 standpoint (e.g., SageMaker, S3, Lambda, Bedrock).

• Understanding of Semantic Data Models and data modeling 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 settings and working across time zones.

🏝️ 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, providing 24/7 confidential assessment, counseling, and referral services

• GE Vernova Retirement Savings Plan

• Tax-advantaged 401(k) savings opportunity with company matching contributions 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