We are looking for a highly skilled and motivated Staff Data Scientist to partner with cross-functional product teams in the development and deployment of cutting-edge AI solutions. This role offers a unique opportunity to work hands-on with large language models (LLMs) and contribute to the optimization of AI-driven products in production environments. As a key player within the AI and ML division, you will play an instrumental role in driving innovation, enhancing product performance, and ensuring the ethical deployment of AI technologies.

Key Responsibilities:

1. Collaborate with diverse teams to design, develop, and implement AI and machine learning solutions, focusing on large language models (LLMs).
2. Build and optimize production-ready LLM systems, ensuring scalability, performance, and reliability.
3. Stay at the forefront of AI innovation by continuously adopting best practices and integrating the latest advancements in AI and machine learning.
4. Conduct thorough evaluations of AI models, performing performance testing and bias assessments to ensure ethical deployment and robust functionality.
5. Provide mentorship and guidance to team members, fostering a collaborative environment while promoting knowledge sharing in AI/ML techniques and deployment best practices.

Qualifications and Experience:

1. A minimum of 7 years of experience applying machine learning techniques to real-world business challenges.
2. Bachelor's or Master's degree in Computer Science, Data Science, Engineering, or a related field.
3. Expertise in the full machine learning model development lifecycle, including experience with frameworks such as Scikit-learn and PyTorch, and with Generative AI technologies like GPT-4.
4. Proficiency in Python and a proven track record of deploying AI/ML models in production environments.
5. Strong experience in model evaluation and optimization, including scalability, reliability, and performance considerations.

Position: Staff Data Scientist
Location: New York
Contract: Permanent
Start Date: By agreement