3 дня назад
Forward Deployed Engineer (AI)
200 000 - 400 000$
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Forward Deployed Engineer (AI): Deploying, integrating, debugging, and optimizing vLLM-powered inference systems across customer cloud, Kubernetes, GPU, networking, and model-serving environments with an accent on production reliability and performance. Focus on solving cross-layer systems problems, optimizing latency and throughput, and turning recurring customer issues into reusable product capabilities.
Location: Based in San Francisco, California; remote work may be considered within the US for exceptional candidates.
Salary: $200,000–$400,000 annual salary plus equity.
Company
develops vLLM-based AI inference infrastructure to make model inference faster and more cost-efficient.
What you will do
- Deploy, integrate, debug, and optimize vLLM-powered inference systems in customer environments.
- Implement solutions across cloud platforms, Kubernetes, GPUs, networking, and model-serving systems.
- Own complex production issues from architecture discussions through implementation and resolution.
- Work with customer engineering teams and core product and engineering teams.
- Convert recurring customer problems into reusable product capabilities, tooling, and platform improvements.
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 languages.
- Production experience deploying or operating ML systems, model serving, AI infrastructure, cloud platforms, Kubernetes, or high-scale backend systems.
- Strong debugging skills across applications, runtimes, infrastructure, networking, identity, storage, observability, and distributed systems.
- Ability to reason about latency, throughput, batching, compatibility, scaling, reliability, and cost in production inference environments.
- Ability to work directly with customer engineering teams and drive ambiguous technical implementations to resolution.
Nice to have
- Experience with vLLM, SGLang, TensorRT-LLM, TGI, Ray Serve, BentoML, or similar inference systems.
- Experience with NVIDIA or AMD GPUs, CUDA, ROCm, GPU scheduling, or multi-GPU serving.
- Experience with enterprise, regulated, security-sensitive, or bring-your-own-cloud deployments.
- Experience building APIs, SDKs, CLIs, deployment platforms, control planes, or infrastructure products.
- Open-source contributions or experience in forward-deployed, customer engineering, field engineering, or technical solutions roles.
Culture & Benefits
- Hands-on engineering role focused on implementation rather than traditional pre-sales.
- Direct influence on customer time-to-value and product evolution.
- Health, dental, and vision benefits.
- 401(k) company match.
- Visa sponsorship available on a case-by-case basis.
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