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Inferact

Open-source LLM inference engine with scalability

Engineering Manager

Engineering LeadershipConfirmed live in the last 24 hours
Full-timeSan Francisco, CA, USA

About the Job

Requirements

  • A bachelor's degree or equivalent experience in computer science, engineering, or a similar field.
  • Demonstrated experience managing strong software engineers in technically demanding systems, infrastructure, machine learning systems, distributed systems, or performance-oriented environments.
  • Strong technical credibility and 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, one-on-ones, 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.
  • A 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.
  • At least two years of management experience with ten or more reports.

Responsibilities

  • Lead a team of engineers across inference systems, performance, kernels, accelerators, and cloud infrastructure.
  • Own team execution, hiring, coaching, prioritization, and operating rhythm while staying close to the technical work.
  • Partner with engineering and company leadership to turn company priorities into clear technical direction.
  • Remove blockers, improve how the team works, and help engineers focus on high-leverage work.

Desired Qualifications

  • Experience leading teams working on AI or machine-learning 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 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.
  • Experience building or scaling a small, unusually high-talent engineering team with a specialized technical scope and a high quality bar.
  • Previous experience as a hands-on engineer or technical lead before moving into management, with the ability to reason credibly about complex production systems.
  • Experience managing teams spanning multiple technical specialties, geographies, or time zones while preserving strong ownership and communication.
  • Experience establishing engineering management practices from an early stage rather than inheriting a mature management system.
  • Contributions to open-source infrastructure, AI systems, developer tools, or technically ambitious products used by external engineers.

About the Company

Inferact

Open-source LLM inference engine with scalability

Inferact builds AI inference infrastructure centered on vLLM, an open-source large language model inference engine. It offers a managed inference service for enterprises with serverless deployment, observability, troubleshooting, disaster recovery, and multi-tenant Kubernetes scaling. vLLM uses PagedAttention to optimize GPU memory, lowering costs and latency while preserving model quality, and Inferact supports new architectures and hardware under vendor-neutral governance with PyTorch Foundation. The goal is to commoditize AI inference and deliver a production-ready operating layer for the AI stack.

Company size
11-50
Company stage
Seed
Total funding
$150M
Headquarters
San Francisco, CA
Founded
2025

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