AI/ML Infrastructure Engineer, GenAI Platform

3 weeks ago


San Francisco, California, United States Magical Tome Full time
About Tome

Tome is a cutting-edge platform that empowers enterprise sellers and account managers to simplify complex research and strategic planning. Our state-of-the-art models leverage thousands of data sources to surface actionable knowledge about customers. A team of experienced sellers, engineers, and researchers tunes and customizes our system to meet the needs of our customers.

About the Role

Tome's AI/ML team is responsible for building the core experiences of our product, developing innovative applications that wow our customers. We're focused on creating a powerful, domain-specific AI that outperforms generic LLMs. As a key member of our team, you'll lead the development of ML product development infrastructure, focusing on scaling and innovating in areas of collaboration and versioning, particularly in the context of LLM model training and prompting.

Key Responsibilities

• Lead the development of ML product development infrastructure, focusing on scaling and innovating in areas of collaboration and versioning, particularly in the context of LLM model training and prompting.
• Create and maintain a platform that will be used by multiple teams working on ML products, ensuring its scalability, efficiency, and user-friendliness.
• Collaborate closely with internal teams to integrate ML solutions and define best practices for software engineering in an AI-driven development landscape.
• Help build a world-class AI/ML engineering team by recruiting and mentoring teammates.
• Address and solve open-ended technological challenges in software engineering at scale, especially in the context of AI-driven systems.

Requirements

• BS or MS degree in CS, Engineering, AI, or a related field.
• 6+ years experience in software engineering with a focus on ML infrastructure.
• Strong understanding of deep learning AI/ML frameworks or cloud services.
• Experience with the integration of software engineering with large language models.
• Ability to navigate and solve open-ended technological challenges in a fast-evolving AI landscape.
• Excellent collaboration skills, with the ability to work effectively with both internal teams and external partners.
• Strong problem-solving skills and the ability to handle complex, cross-functional projects.

Bonus Points

• Publications in applied AI/ML scientific journals.
• Experience navigating open source/vendor solutions in LLM ops space (LangChain, Llama, Pinecone, etc).

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