资深软件工程师,AI推理网关
Staff Software Engineer, AI Inference Gateway
我们的使命是让云计算民主化
通过利用消费者的闲置资源,为每个人打造一个可持续、可负担、环保的云服务
salad.com/about
AI推理网关资深软件工程师
Salad Technologies · 远程办公 · 全职
职位描述
SaladCloud 在数千个分布在全球的工作站和消费者GPU(NVIDIA和AMD)上运行推理——这些资源没人能用。在这些资源前面是一个用Rust编写的独特AI网关,基于Pingora和WireGuard构建,为客户提供单一可靠的API,支持实时和批量推理及嵌入。你将负责维护它。
这是一个具有真正自主权的基础设施岗位。你将设计并交付决定请求如何完成、何时增加或减少容量以及如何按每个token计费的系统——你将是那个知道新模型、量化或GPU是否值得运行的人。
你将负责
· 全程负责AI网关系统:请求路由、流处理、批量/异步任务处理以及跨多个网关服务器的横向扩展
· 构建和优化舰队效率算法——自动扩展节点、评估性能,并驱逐表现不佳的节点,使网络在每美元成本下达到最大吞吐量
· 运维和扩展运行vLLM、llama.cpp等服务器的底层推理节点
· 设计并维护基于OpenTelemetry的网关和舰队可观测性;按token计费和订阅计费已经基于此遥测数据,因此你需要确保该集成准确无误
· 大约花费25%的时间对新模型、量化和GPU硬件进行基准测试,并与产品和市场团队合作决定哪些内容进入生产环境
· 与其他Salad工程团队协作进行跨系统设计和集成;向技术和非技术人员清晰解释权衡
团队
你将加入一个小型团队——五名工程师加上仍会写代码的CTO,以及两名深入技术的产品经理,他们自己会提交修复而不是把问题排到你这里。你将直接向CTO汇报。工程团队中的每个人都拥有10年以上经验,并且已经构建了在大规模下运行的系统——因为我们在第一次发布时就确保了系统的生产可用性,因此每年的事故极少。
你将是第一位具备推理网关经验的员工,你将负责整个领域。你不会独自完成:你的
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Our mission is to democratize cloud computing
by utilizing latent consumer resources to power a sustainable, affordable, environmentally friendly cloud for everyone.
salad.com/about
Staff Software Engineer, AI Inference Gateway
Salad Technologies · Remote · Full-time
The role
SaladCloud runs inference on thousands of geodistributed workstation and consumer GPUs — NVIDIA and AMD — that nobody else can use. Sitting in front of that fleet is a unique AI Gateway written in Rust, built on Pingora and WireGuard, that serves real-time and batch inference and embeddings to customers as a single, reliable API. You'll own it.
This is an infrastructure role with real autonomy. You'll design and ship the systems that decide how requests are fulfilled, when to add or drop capacity, and how to bill for every token — and you'll be the person who knows whether a new model, quantization, or GPU is actually worth running.
What you'll do
- Own the AI Gateway system end to end: request routing, streaming, batch/async job handling, and horizontal scaling across multiple gateway servers
- Build and tune the fleet-efficiency algorithms — autoscaling nodes, scoring performance, and evicting underperformers so the network converges on peak throughput per dollar
- Operate and scale the underlying inference nodes running vLLM, llama.cpp, and similar servers
- Design and maintain OpenTelemetry-based observability across the gateway and the fleet; pay-per-token and subscription billing already rides on this telemetry, so you'll keep that integration accurate
- Spend roughly 25% of your time benchmarking new models, quantizations, and GPU hardware, and work with the product and marketing teams to make the call on what goes into production
- Collaborate on cross-system design and integrations with the rest of Salad engineering; explain trade-offs clearly to both technical and non-technical teammates
The team
You'll join a small team — five engineers plus the CTO, who still writes code, and two deeply technical product managers who ship their own fixes rather than queue them for you. You'll report directly to the CTO. Everyone on the engineering team has 10+ years of experience and has built systems that already run at massive scale — with minimal incidents in a typical year, because we ship things that are production-worthy the first time.
You'll be the first hire with inference-gateway expertise and you'll be asked to own the whole surface. You won't do it alone: your teammates are eager to learn the domain, will pair on design and integrations, and share after-hours support. The bar is high; so is the support.
We've listed a lot below. If you're strong in two of the first three — Rust, LLM inference servers, distributed systems — apply, and expect to learn the rest fast with people who'll help.
What we're looking for
- Strong production Rust experience, ideally on high-throughput networked services
- Hands-on experience running LLM inference servers (vLLM, llama.cpp, TGI, TensorRT-LLM, or similar) — you know what a KV cache is and why it fills up
- Distributed systems fundamentals: load balancing, backpressure, failure handling, unreliable nodes
- Comfort operating what you build: metrics, tracing, on-call instincts
- Willing to be on-call for a system you helped make quiet — we treat after-hours pages as a design bug to fix, not a lifestyle
- Clear written and verbal communication; you can run a design without hand-holding and bring others along
Nice to have
- Pingora, Tokio, or proxy/gateway internals
- Experience with heterogeneous or consumer-grade GPU fleets, CUDA, or ROCm
- Quantization formats (GGUF, AWQ, GPTQ, FP8) and their performance characteristics
Why Salad
You'll work on a hard, unusual problem — coaxing datacenter-grade reliability out of hardware in people's homes — with the freedom to make major decisions and see them hit production quickly.
We're scaling rapidly: demand for inference on SaladCloud currently exceeds the capacity we can bring online, and this role exists to keep up with it. There is no shortage of work and no prospect of it ramping down.
The platform handles workload security and isolation, so you can focus on performance. We don't log or train on our customers' prompts or data.
Benefits
- Unlimited PTO
- 75% of health insurance premiums covered for you and your dependents
- Dental and vision coverage
- 401(k) plan
- Stock options
- Company-provided computer
- $500 WFH budget
- Fully remote, with flexible hours
Compensation
$180,000-$220,000/year
Originally posted on Himalayas