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GE Vernova
AI

AI Engineer

GE Vernova · Bellevue, WA, US · $108k - $162k

Actively hiring Posted about 1 month ago

Responsibilities

  • Assist in developing components of AI agent frameworks, including orchestration workflows, tool integrations, and basic state management.
  • Build and maintain backend services in Python (or Java/Go/C++) to support AI inference and data processing.
  • Support development of LLM-based applications, including prompt design, tool usage, and evaluation workflows.
  • Contribute to model integration and deployment, including working with APIs and inference endpoints.
  • Help develop microservices and data pipelines for processing time-series and streaming data.
  • Assist in integrating AI services with grid systems such as SCADA and simulation tools.
  • Participate in performance tuning and debugging of distributed systems under guidance.
  • Contribute to CI/CD pipelines, testing, and monitoring for AI services.
  • Implement logging and basic explainability features for AI outputs.
  • Collaborate in code reviews and contribute to shared codebases following engineering best practices.

Basic qualifications

  • Bachelor’s or Master’s degree in Computer Science, AI/ML, or a related field.
  • 0–3 years of software development or AI/ML experience (internships/projects included).

Preferred qualifications

  • Proficiency in Python; exposure to Java, C++, or Go is a plus.
  • Basic understanding of machine learning concepts and LLM applications.
  • Familiarity with APIs, backend development, and microservices concepts.
  • Exposure to cloud, containers (Docker), or orchestration (Kubernetes) is a plus.
  • Understanding of data structures, algorithms, and software engineering fundamentals.
  • Interest in distributed systems and real-time data processing.
  • Familiarity with power systems (EMS, DMS, SCADA) is a plus but not required.
  • Hands-on experience building production AI systems in a mission-critical domain.
  • Mentorship from experienced engineers in AI, distributed systems, and grid software.
  • Exposure to real-world applications of AI in energy and infrastructure.
  • Opportunities to grow into more advanced engineering roles.

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