Salary

$200K–$400K

Type

Full-time

Experience

2+ yr

Visa sponsorship

Sponsorship mentioned

About this role

Overview

Inferact's mission is to grow vLLM as the world's AI inference engine and accelerate AI progress by making inference cheaper and faster. Founded by the creators and core maintainers of vLLM, we sit at the intersection of models and hardware, a position that took years to build.

About the Role

We're looking for an Engineering Manager to help scale a world-class, senior-heavy engineering organization working at the frontier of AI inference. You will lead a team of exceptional engineers across areas such as inference systems, performance, kernels, accelerators, and cloud infrastructure while creating the management capacity required for Inferact to keep growing quickly without sacrificing technical quality or execution speed.

This is a deeply technical management role. You will own team execution, hiring, coaching, prioritization, and operating rhythm, while staying close enough to the work to earn the trust of engineers solving hard systems problems. You will partner closely with engineering and company leadership to turn company priorities into clear technical direction, remove blockers, improve how the team works, and help every engineer do the highest-leverage work of their career.

Skills and Qualifications

Minimum qualifications:

Bachelor's degree or equivalent experience in computer science, engineering, or similar.

Demonstrated experience managing strong software engineers in technically demanding systems, infrastructure, ML systems, distributed systems, or performance-oriented environments.

Strong technical credibility with the ability to understand architecture, ask useful questions, challenge assumptions, and help unblock senior engineers without becoming a bottleneck or overriding domain experts.

Experience owning the full people-management lifecycle, including hiring, onboarding, 1:1s, feedback, performance management, career development, team health, and retention.

Ability to translate ambiguous company priorities into clear team goals, sequencing, ownership, and execution plans while maintaining urgency in a fast-changing startup environment.

Track record of building effective engineering operating rhythms around planning, decision-making, technical reviews, cross-team coordination, and accountability without creating unnecessary process.

Strong judgment about when to dive into a technical problem, when to delegate, and how to create leverage for senior engineers rather than competing with them for ownership.

2+ years of management experience with 10+ reports.

Preferred qualifications:

Experience leading teams working on AI / ML infrastructure, model serving, distributed systems, GPU infrastructure, compilers, performance engineering, cloud infrastructure, or developer platforms.

Experience managing senior, staff, principal, research-adjacent, or PhD engineers in an environment where technical credibility and autonomy are especially important.

Experience scaling an engineering team through rapid hiring, including interviewer calibration, hiring decisions, onboarding systems, and thoughtful team design.

Familiarity with inference systems and adjacent technologies such as vLLM, SGLang, PyTorch, CUDA / Triton, Kubernetes, distributed serving, or accelerator infrastructure.

Experience partnering closely with founders or engineering executives in an early-stage company where priorities, team boundaries, and organizational needs evolve quickly.

Bonus points if you have:

Built or scaled a small, unusually high-talent engineering team where the technical surface area was specialized and the quality bar was extremely high.

Previously remained hands-on as an engineer or technical lead before moving into management and can still reason credibly about complex production systems.

Managed teams spanning multiple technical specialties, geographies, or time zones while preserving strong ownership and communication.

Helped establish engineering management practices from an early stage rather than inheriting a mature management system.

Contributed to open-source infrastructure, AI systems, developer tools, or technically ambitious products used by external engineers.

Logistics

Location: This role is based in San Francisco, California and is in-office.

Compensation: Depending on background, skills, and experience, the expected annual salary range for this position is $200,000 - $400,000 USD + equity.