Job responsibilities
- Lead optimization of generative AI models, focusing on large language models (LLMs) and retrieval-augmented generation (RAG).
- Collaborate with cross-functional teams to integrate AI solutions into business processes and intelligent solutions.
- Conduct data preprocessing, transformation, and feature engineering for AI model training and analysis.
- Develop and implement data transformation pipelines to ensure data quality and accessibility.
- Deploy and manage AI models using frameworks like PyTorch and TensorFlow.
- Stay updated on advancements in AI and machine learning, applying new techniques to improve model performance.
- Participate in Agile teams, contributing to sprint planning, stand-ups, and retrospectives for timely AI solution delivery.
Required qualifications, capabilities, and skills
- Formal training or certification on software engineering concepts and 2+ years applied experience
- Demonstrate advanced proficiency in Python and experience with machine learning libraries and frameworks.
- Have proven experience in training and fine-tuning generative AI models, including large language models (LLMs) and retrieval-augmented generation (RAG).
- Exhibit a strong understanding of deep learning concepts and techniques, especially in the context of generative AI.
- Experience working on enterprise-scale machine learning projects in a professional environment.
- Expertise in data transformation, preprocessing, and feature engineering techniques.
- Proficient in using PyTorch and TensorFlow for deploying generative AI models.
Preferred qualifications, capabilities, and skills
- Familiarity with automation tools like Alteryx
- Bachelor's degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field.
- Exposure to cloud technologies