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Inference Engineering and Product Lead
Summary by AIEngineer.careers
Inference Engineering and Product Lead is a AI Infrastructure Engineer role (full-time). with Modal. in SAN FRANCISCO, US. Imported listing (source: emploive.com). Apply on the employer's site (emploive.com).
Imported listing (source: emploive.com) · Apply on emploive.com
SAN FRANCISCO · US
—
Full-time
DIRECTOR
The sections below reproduce the third-party job description for reference. AIEngineer.careers does not write or control this text.
Imported job description
Sourced from emploive.com
Modal is seeking a Director-level leader to own the direction and execution of its LLM inference platform. This hands-on leadership role combines technical contribution, product strategy, and people management to maintain market leadership in AI infrastructure. The ideal candidate will drive performance optimization for frontier models while building a high-performing engineering team.
Responsibilities
- Recruit, hire, and grow a high-performing team of engineers with a focus on coaching and career growth.
- Drive technical and product decisions through design reviews, code reviews, and architectural discussions.
- Lead efforts working with customers on novel or frontier workloads to ensure success on Modal's platform.
- Translate learnings from frontier customers into a roadmap for internal optimization and user-facing products.
- Partner with business operations on compute strategy and collaborate with GTM on product launches.
Requirements
- 10+ years of industry experience, including 3+ years in a leadership role.
- Track record of building high-performance systems at scale.
- Strong background in cloud infrastructure.
- Deep knowledge of low-level OS foundations (Linux kernel, file systems, containers).
Modal
New York · US · 221+ employees
Modal is an AI infrastructure company that provides a cloud platform for developers to run compute-intensive tasks. It offers serverless execution for workloads such as AI inference, model training, batch processing, and secure sandboxes, allowing users to scale resources instantly without managing underlying infrastructure.
