Artificial Intelligence / Machine Learning Lead Engineer

About the role

Required qualifications

• At least 10 years of overall professional experience, including at least four years working with artificial intelligence, generative artificial intelligence or agent-based artificial intelligence.
• Hands-on experience with large language models, prompting techniques, structured outputs, model routing, context management, memory management and retrieval-augmented generation.
• Strong proficiency in Python and experience with machine learning frameworks and libraries such as scikit-learn, TensorFlow, PyTorch, Keras or pandas.
• Experience with vector databases, retrieval systems, cloud platforms such as Amazon Web Services, Google Cloud or Microsoft Azure, and services built with Flask or FastAPI.
• Bachelor's degree in engineering or a related field, or an equivalent combination of education, training and work experience.

Preferred qualifications

• Experience fine-tuning large language models, including parameter-efficient approaches such as low-rank adaptation and quantized low-rank adaptation.
• Familiarity with orchestration tools such as LangChain, LlamaIndex, AutoGen or the OpenAI Assistants application programming interface.
• Knowledge of production machine learning operations, continuous integration and delivery, monitoring, observability, security, compliance and data governance.
• The impact you'll make
• The FIS artificial intelligence and machine learning team identifies, explores and implements solutions designed to support revenue growth and operational savings. The team brings together solution architects, data scientists and machine learning engineers. As an Artificial Intelligence and Machine Learning Engineer Lead, you will help turn emerging technologies into practical solutions that can be applied across the organization.
• What we offer you
• At FIS, your career journey is yours to shape. We provide the tools, experiences and support to help you reach what's next.
• Here's what else we offer:
• Opportunities to make an impact in fintech
• Internal career growth opportunities
• Personal and professional learning
• Inclusive, diverse work environment
• Resources to give back to your community