As a Generative AI Application Developer specializing in Large Language Models (LLMs), you will be responsible for creating advanced generative AI applications, including but not limited to Chatbots, Retrieval Augmented Generation (RAG), report automation, and fine-tuned models. You will work closely with cross-functional teams to seamlessly integrate generative AI tools and systems. Your expertise will be crucial in driving the success of our AI initiatives and fostering innovation within the organization.

About National Oilwell Varco
Every single day, we put the oil and gas industry’s best minds and more than 150 years of experience to work to help our customers achieve lasting success. We have the people, capabilities, and vision to serve the needs of a significant and evolving industry. One the world can’t live without. 
Throughout every region in the world, and across every area of drilling and production, our company provides the technical expertise, advanced equipment and operational support necessary for success – now and in the future.
 

At NOV, we power the people who power the world.

Your Responsibilities:

• Collaborate closely with product, technology, and data science teams to ensure the seamless integration of generative AI tools and systems
• Develop generative AI applications, particularly Large Language Models (LLM), using techniques such as Retrieval Augmented Generation (RAG), fine-tuning, and prompt engineering
• Create and process datasets for Generative AI applications
• Design and prototype model workflows utilizing relevant cloud resources (any of Azure, AWS, GCP, Databricks, etc.)
• Deploy the Generative application in a web application (container or server)  or business intelligence environment
• Evaluate and monitor the performance and output quality of generative AI models
• Stay updated with the latest trends and developments in Generative AI (LLM) and apply this knowledge to improve internal processes and customer services.

Required Qualifications:

• Bachelor’s degree in computer science, engineering, mathematics, or equivalent
• 2+ years of experience in industry designing, implementing, or consulting on developing Large Language Model applications, including modeling, evaluation, and integration
• 5+ years of experience in industry specific technology domain areas (e.g., software development, cloud solution architecture, data & analytics)
• Strong understanding of Generative AI models, concepts, capabilities, and usage patterns
• Proven expertise in architecting and prototyping systems using generative AI technologies
• Full stack development experience is necessary. Such as strong Python and prototyping web applications (React, JavaScript)
• Exceptional communication skills to articulate technical concepts to non-technical stakeholders and facilitate effective collaboration across different departments

Preferred Qualifications, Capabilities, And Skills

• Master’s degree in computer science, engineering, mathematics, or equivalent.
• Expertise in NLP with deep learning application experience is a plus
• Experience with LangChain or other similar abstraction/orchestration library is a plus
• Proficiency with HuggingFace or other platforms is a plus
• Understanding with data science and machine learning lifecycle (MLOps) is a plus
• API development experience is a plus
• Knowledge of compliance with industry standards and regulations, data governance and security, and responsible AI practices is a plus
   

We are an equal opportunity employer.
National Oilwell Varco is committed to building a diverse environment and is proud to be an equal opportunity employer. We do not discriminate on the basis of race, color, religion, sex, national origin, disability status, protected veteran status, sexual orientation or any other characteristic protected by law.
We offer a comprehensive employee benefit package including health, life, and disability insurance; a retirement plan; and paid time off. Our company is committed to crafting a lasting impact for ourselves, our customers, and the communities where we live and work.