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Lead Engineer – Generative AI & Prompt Engineering
| Company | GE Vernova |
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| Location | Schenectady, NY, USA |
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| Salary | $98200 – $164000 |
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| Type | Full-Time |
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| Degrees | Bachelor’s, Master’s |
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| Experience Level | Senior, Expert or higher |
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Requirements
- Bachelor’s degree in Computer Science, Engineering, Mathematics, or related field with 5+ years’ relevant experience.
- Experience with prompt engineering and familiarity with tools such as OpenAI’s GPT models, Hugging Face, etc.
- Proficiency in Python or other programming languages commonly used in AI/ML development.
- Strong problem-solving skills and attention to detail.
- Excellent communication skills, with the ability to articulate complex technical concepts to non-technical stakeholders.
- Ability to work collaboratively in a team environment and adapt to changing project requirements.
- Candidate must be willing to travel a minimum of 2 weeks per year.
- Must be 18 years or older.
- Legal authorization to work in the U.S. is required. We will not sponsor individuals at the Bachelor’s nor Master’s level for employment visas, now or in the future, for this job opening.
- You must submit your application for employment on the careers page at www.gecareers.com to be considered.
- Must be willing to work out of an office located in Niskayuna, NY.
Responsibilities
- Collaborate with domain experts to understand business needs and translate them into clear and effective LLM prompts.
- Develop, test, and refine prompts for a variety of use cases, ensuring high accuracy and relevance in generated outputs.
- Work closely with software developers to integrate LLM solutions into existing or new applications.
- Contribute to the development of a scalable framework for prompt engineering, promoting reuse and knowledge sharing across different business units.
- Assist in gathering and analyzing user feedback to continually improve prompt effectiveness.
- Stay up-to-date with advancements in LLM technology and contribute to strategic decisions on tool and platform selection.
- Document prompt engineering processes, best practices, and use case outcomes to build a comprehensive knowledge base.
Preferred Qualifications
- Master’s degree in Computer Science, Engineering, Data Science, or related field
- Experience with machine learning frameworks (e.g., PyTorch) and data processing libraries (e.g., Pandas, NumPy).
- Previous experience or internships involving NLP or machine learning projects.
- Familiarity with version control systems like Git.
- Understanding of traditional industry operations and challenges.
