Modal
AI & Machine LearningDirect Ashby career site

Inference Engineering and Product Lead

Location
San Francisco, CA · On-site
Job type
Full-time
Level
Director
Experience
10+ years
Listed
30 days ago

Skills & highlights for this role

  • LLM inference serving
  • distributed computing
  • Linux kernel
  • containers
  • cloud infrastructure

Also useful

  • KV cache management
  • speculative decoding
  • GPU memory snapshots

The Role

Modal's LLM inference platform delivers frontier performance for open-source models with best-in-class elasticity and developer experience, made in part possible by our custom runtime with GPU memory snapshots and multi-cloud substrate

We're looking for a leader to own the direction and execution of this platform to continue to establish us as the clear market leader, working closely with customers like Cognition, Doordash, Ramp, and many more. You'll be leading a group of highly talented engineers working on our market-leading LLM inference offering, spanning the serving stack, routing infrastructure, internal agentic optimization platform, and the user-facing product surface area.

This is a hands-on leadership role - expect to split your time between technical contribution, product shaping and people management depending on what the team needs. You'll set direction, remove blockers, and build a strong engineering culture as your team tackles hard problems in distributed computing, frontier inference serving, and performance optimization.

Responsibilities

Team

  • Recruit, hire, and grow a high-performing team of engineers; run regular 1:1s focused on coaching, feedback, and career growth.
  • Set clear performance expectations, hold a high bar, and build an environment where engineers do their best work.
  • Foster a culture of ownership, accountability, customer obsession, and continuous improvement.

Technical and Product Direction

  • Drive technical and product decisions through design reviews, code reviews, and architectural discussions.
  • Lead our efforts working with customers with novel or frontier workloads so they can be successful running on Modal.
  • Translate learnings from frontier customers into a roadmap for our internal optimization platform and user-facing product, so that gains from optimization and research efforts are accessible to all of our users.
  • Establish standards for reliability and product excellence; ensure the team owns projects end-to-end, from spec through production.

Cross-Functional Leadership

  • Partner with business operations and compute strategy on continuing to develop our strategy for compute purchases across a variety of accelerators.
  • Collaborate with GTM on product launches, positioning, and improving win rates for inference opportunities.
  • Help guide the roadmap for teams building the infrastructure platform underlying inference, as well as adjacent product teams.

Requirements

  • 10+ years of industry experience, including 3+ years in a leadership role
  • Track record building high-performance systems at scale
  • Strong background in cloud infrastructure
  • Deep knowledge of low-level OS foundations (Linux kernel, file systems, containers, etc.)
  • Nice to have: Experience working with LLM inference in production and familiarity with underlying concepts like engines, kernels, routing, KV cache management and speculative decoding.

About US

AI needs a new infrastructure layer. We're building it at Modal.

Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now.

Our customers include category-defining companies like Lovable Ramp Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale.

We recently raised a $355M Series C at a $4.65B valuation, led by General Catalyst and Redpoint Ventures. We've crossed $300M+ ARR and grown fivefold since September.

Our team includes creators of popular open-source projects (e.g.,Seaborn), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience.

Read the original posting

From Modal's careers page, first listed on Rolev.ai on October 10, 2026. Rolev.ai is not the employer.

How Rolev.ai helps with this application

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Common questions

Where is the Inference Engineering and Product Lead job at Modal located?

This Inference Engineering and Product Lead position at Modal is located in San Francisco, CA (On-site). Always check Modal's application page for specific state eligibility or relocation policies.

What qualifications are required for Inference Engineering and Product Lead at Modal?

For the Inference Engineering and Product Lead role, Modal highlights 10+ years of relevant experience; experience with LLM inference serving, distributed computing, Linux kernel, containers, cloud infrastructure. Rolev.ai can score your existing resume against these requirements and show any skill gaps before you apply.

How do I apply for the Inference Engineering and Product Lead position at Modal?

This listing links directly to Modal's Ashby application page. You can apply directly on Modal's site, or use Rolev.ai to check your resume fit, generate a zero-hallucination tailored resume and cover letter for this posting, and autofill the Ashby application form in 1 click with the Rolev.ai Chrome extension. You always review the form and press Submit yourself.