Senior Generative AI Research Engineer
NVIDIAFull Time
Senior (5 to 8 years), Expert & Leadership (9+ years)
Candidates must possess a Bachelor's degree in a quantitative discipline or a Master's degree in a similar field, coupled with at least 5 years of professional experience. Required skills include 7+ years of Python application development with data manipulation libraries like Pandas and NumPy, familiarity with API frameworks (FastAPI, Flask) and RESTful APIs, a strong understanding of machine learning frameworks (TensorFlow, PyTorch, Scikit-learn), and familiarity with cloud platforms (AWS, Google Cloud, Azure). Additionally, 3+ years of experience with containerization (Docker, Kubernetes) and CI/CD tools, experience working with Large Language Models (LLMs) in application development, and experience with version control systems (Git) and software development best practices are necessary. Preferred qualifications include knowledge of generative AI frameworks like Langchain or Pydantic AI, experience deploying software with Docker and Kubernetes, experience with deep learning techniques, knowledge of natural language processing (NLP), and familiarity with big data technologies (Hadoop, Spark).
The Lead AI Engineer will explore and implement generative AI technologies using Large Language Models and other generative models to create innovative solutions. Responsibilities include building and maintaining robust APIs for Retrieval-Augmented Generation and generative AI agents, designing, developing, and maintaining data pipelines for large datasets, and assisting the data science team in developing and deploying traditional machine learning models. The role involves collaborating with data scientists to understand model requirements and translate them into scalable engineering solutions, as well as monitoring and maintaining the performance and reliability of deployed APIs, models, and data pipelines. Staying up-to-date with the latest advancements in AI and related technologies is also a key responsibility.
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