About TomeTome is a unified platform for enterprise sellers and account managers.We use state-of-the-art models to simplify complex research and strategic planning for sellers. Tome can surface the most actionable knowledge about a customer from within internal systems as well as from public information across thousands of data sources.Our system is tuned and customized by a team of experienced sellers, engineers, and researchers. Many of us worked on large-scale products at Llama, Messenger, Instagram, and LinkedIn before this.We design and build Tome in close partnership with our early customers-many of whom are mature enterprise sales orgs. We'll continue to work this way to ensure we build an enduring solution to longstanding problems in the industry.About the roleTome's AI/ML team builds the experiences at the core of our product, developing new applications to wow our customers.Today, the team focused on building a powerful, domain-specific AI that outperforms generic LLMsWe're inspired by the challenge of creating innovative new AI products for people doing serious work, and we're looking to grow our AI/ML team to meet that challenge.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.
Who You Are
- You have a BS or MS degree in CS, Engineering, AI or a related field.
- 6+ years experience in software engineering with a focus on ML infrastructure.
- You have a 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)