About the Role

Zep is building the long-term memory layer for the LLM application stack. We have a large and active open-source community and recently launched our cloud service. We’re seeking an experienced AI Engineer to join our startup. As a critical member of our small, fast-paced team, you will design, implement, and maintain our Go-based APIs.

We are a remote-first organization. Zep is funded by YC, Engineering Capital, and angels such as Guillermo Rauch (Vercel).

Key Responsibilities:

Lead the development, implementation, and optimization of LLM-based AI solutions
Design and execute training strategies for LLMs, including data preparation and model fine-tuning
Develop and implement rigorous testing and validation protocols for AI models
Collaborate with cross-functional teams to integrate AI solutions into our products
Stay current with the latest advancements in AI and LLM technologies
Make critical decisions regarding AI architecture, model selection, and implementation strategies
Manage end-to-end project lifecycles with minimal supervision
Contribute to the company's AI strategy and vision

Required Qualifications:

Bachelor's or Master's degree in Computer Science, AI, Machine Learning, or a related field
Minimum 12-months experience advanced work with LLMs: agentic applications, advanced RAG, structured output, and more
Minimum of 5 years of hands-on experience with machine learning, including training, testing, deploying, and validation
Strong programming skills in Python and familiarity with deep learning frameworks such as PyTorch or TensorFlow
Extensive knowledge of natural language processing techniques and architectures
Experience with cloud computing platforms (e.g., AWS, GCP, Azure) for AI model deployment
Comfortable with ambiguity and thrives in a fast-paced, evolving environment

Nice to Have

Contributions to open-source projects, particularly LLM-related
Experience in REST API development, NoSQL database design, and RDBMS design and optimizations
Experience with Go or TypeScript

Benefits

Directly impact the development of the future LLM application stack
Competitive salary and equity compensation
Flexible work hours and remote work options
Health, dental, and vision insurance
Opportunities for professional growth and development
Collaborative and inclusive work environment

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