Impress employers and recruiters.
Choose from hundreds of resume examples.

Target Resume Now

Tailor your resume to this Member of Technical Staff, Forward Deployed Engineer role.

Rezi rewrites your resume against Inferact's job description. Free.

Resume score gauge reading 58 out of 100

Don't guess if your resume is good enough.

See how it scores against the Member of Technical Staff, Forward Deployed Engineer posting at Inferact — free, in seconds.

About the Role

We are seeking a Forward Deployed Engineer to ensure the success of Inferact within customer environments. You will collaborate with customers on deploying, integrating, debugging, and optimizing vLLM-powered inference systems across various platforms including cloud, Kubernetes, GPU, networking, and model-serving environments. This is a hands-on engineering role focused on implementation, owning production issues, and translating field learnings into product enhancements.

Responsibilities

Deploy, integrate, debug, and optimize vLLM-powered inference systems.
Work directly with customers to address their technical needs.
Own difficult production problems end-to-end.
Collaborate with core product and engineering teams to inform product development.
Translate field learnings into reusable product capabilities.
Contribute to the evolution of Inferact's platform.

Requirements

Bachelor's degree or equivalent experience in computer science, engineering, systems, machine learning, or a related field.
Strong software engineering skills in Python, Go, TypeScript, or similar.
Experience building production-quality integrations, tooling, services, automation, or prototypes.
Hands-on experience deploying or operating ML systems, model serving, AI infrastructure, cloud platforms, Kubernetes, or high-scale backend systems in production.
Ability to work with sophisticated customer engineering teams and navigate ambiguous technical environments.
Ability to personally drive implementations and debugging to resolution.
Strong systems debugging skills across application, runtime, infrastructure, networking, identity, storage, observability, and distributed-system boundaries.
Ability to reason about latency, throughput, batching, model/runtime compatibility, scaling, reliability, and cost tradeoffs in production inference environments.
High ownership and strong technical communication skills.
Judgment to distinguish one-off customer work from problems that should become reusable product capabilities.

Skills

Python
Go
TypeScript
ML systems deployment
Model serving
AI infrastructure
Cloud platforms
Kubernetes
High-scale backend systems
Systems debugging
vLLM
SGLang
TensorRT-LLM
TGI
Ray Serve
BentoML
NVIDIA GPUs
AMD GPUs
CUDA
ROCm
GPU scheduling
Multi-GPU serving
Accelerator-backed infrastructure
Enterprise software deployment
APIs
SDKs
CLIs
Developer tooling
Deployment platforms
Control planes
Infrastructure products
Performance profiling
Open-source ML systems
Inference infrastructure
Cloud infrastructure
Kubernetes
Developer tooling
Customer engineering
Field engineering
Solutions architecture
Deployment playbooks
Reference architectures
Automation
Production issue resolution

Location

San Francisco, California
Remote in the US

Work Type

Full-time

Experience Level

Senior

Education Level

Bachelor's degree or equivalent experience

Salary/Compensations

$200,000 - $400,000 USD + equity

Benefits

Health benefits
Dental benefits
Vision benefits
401(k) company match

About the Company

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.