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Inferact

Open-source LLM inference engine with scalability

Developer Relations Engineer - Developer Relations

Developer Relations & AdvocacyConfirmed live in the last 24 hours
Full-time

About the Job

Requirements

  • A bachelor's degree or equivalent experience in computer science, engineering, machine learning, systems, or a similar field.
  • Strong technical understanding of large language model inference systems, model serving, GPU inference, distributed runtimes, scheduling, batching, quantization, or related infrastructure.
  • Ability to credibly explain systems concepts such as KV cache, PagedAttention, continuous batching, prefill/decode scheduling, prefix caching, speculative decoding, tensor parallelism, data parallelism, or latency-versus-throughput tradeoffs.
  • Experience with vLLM or adjacent inference technologies such as SGLang, TensorRT-LLM, TGI, LoRAX, Ray Serve, FlashInfer, BentoML, Baseten-style serving platforms, or similar systems.
  • A strong public portfolio of technical artifacts, such as blogs, tutorials, workshops, courses, open-source documentation, benchmark posts, architecture explainers, conference talks, demos, or runnable repositories.
  • Ability to write and teach for practitioners without sounding like a content marketer.
  • Strong engineering judgment, product taste, and ability to turn raw technical material into useful developer education.

Responsibilities

  • Write technical deep dives, build demos, create tutorials, contribute to documentation and examples, host workshops, and help developers understand inference topics including KV cache, continuous batching, prefix caching, prefill and decode, quantization, GPU serving, latency versus throughput, and model-server tradeoffs across vLLM and adjacent systems.
  • Shape how the broader AI infrastructure community learns, adopts, and builds with vLLM.

Desired Qualifications

  • Prior work in machine learning systems, distributed systems, high-performance computing, compilers, GPU kernels, serving infrastructure, MLOps, developer tooling, or open-source infrastructure.
  • Experience creating technical content that teaches reusable mental models, not just product features.
  • Experience contributing to developer-facing open source through documentation, tutorials, examples, cookbooks, demos, or community support.
  • Existing credibility or community presence in AI infrastructure, open-source software, CUDA/GPU, Ray, vLLM, PyTorch, Modal, BentoML, Baseten, Predibase, Together AI, Anyscale, LMSYS, or similar ecosystems.
  • Ability to host workshops, create hands-on labs, present technical talks, and help developers move from concept to working code.
  • Written widely-shared technical blogs, courses, or architecture deep dives on LLM inference, model serving, GPU serving, or machine learning systems.
  • Built demos, benchmarks, tutorials, or repositories around vLLM, SGLang, TensorRT-LLM, TGI, Ray Serve, FlashInfer, or related systems.
  • Contributed to open-source machine learning infrastructure, inference systems, developer tooling, or technical education projects.
  • Created practitioner-facing content with code, diagrams, benchmarks, demos, or end-to-end labs.
  • Built a durable personal portfolio that demonstrates technical depth, taste, and a strong point of view.

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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