ABOUT YUPP

We are a well-funded, rapidly growing, early-stage AI startup headquartered in Silicon Valley that is building a two-sided product - one side meant for global consumers and the other side for AI builders and researchers. We work on the cutting edge of AI across the stack. Check out our product that was launched recently, and how it solves the foundational challenge of robust and trustworthy AI model evaluations. Here’s more information about us.

QUALIFICATIONS

• Bachelor’s or Master’s degree in Computer Science, Engineering, Mathematics, or a related field (Ph.D. or equivalent experience is a plus).
• Minimum of 10 years of experience in machine learning, with proven success deploying AI models in real-world applications.
• Strong programming skills in Python, with familiarity in libraries such as PyTorch, TensorFlow, NumPy, and JAX.
• Deep understanding of machine learning algorithms, data structures, and model evaluation methodologies.
• Strong background in modern LLM architectures and applications, and experience in using GenAI approaches in an applied, production environment.
• Excellent communication and presentation skills, with the ability to clearly explain design decisions.
• Strong analytical and problem-solving skills, able to work independently and collaboratively in a fast-paced environment.

PREFERRED QUALIFICATIONS

• Authored or co-authored research papers in reputable AI/ML conferences or impactful technical blog posts.
• Active participation in open-source AI/ML repositories, Kaggle competitions, or similar projects.
• Experience working in startup or small, fast-paced environments.

• Stay up to date on emerging trends in GenAI and LLM advancements, identifying opportunities for application within the company.
• Design, build, and maintain LLM applications that meet high performance and reliability standards.
• Own the full ML lifecycle, including data analysis, preprocessing, model architecture, training, evaluation, and MLOps.
• Collaborate with product engineers, designers, and data scientists to develop cutting-edge AI solutions.
• Communicate complex technical concepts clearly to both AI experts and non-technical audiences.
• Troubleshoot, debug, and optimize AI models for scalability and efficiency.
• Write clean, maintainable, and well-documented production code.