FluidstackBuilds for teams inside the company
Decision Engineer, Business Operations
San Francisco, CAOn-site
$224,000–$300,000
Published · Updated
$150,000–$400,000San Jose, CAOn-site
Identify production bottlenecks and own solutions from concept through daily adoption
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$150K–$400KAbove the median
Median $190K
This job$150K–$400KTypical senior FDE payMiddle 50% of 1,789 postings$160K–$220KBuilds for teams inside the company
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Posted by Etched on
Our Internal Acceleration team’s mandate is to build agents to accelerate the production of frontier tokens.
You’ll work directly with our founders and embed with our production team to build new agentic harnesses and operating systems to transform the way hardware is built in an AI native world. Your work will vary widely, and your success is measured by how much faster Etched moves, not by the lines of code you write.
This role is for engineers who thrive on ambiguity, have real product sense, and want to own problems end to end. It’s a whiteboard for future founders. The problems we solve are time-sensitive and business-critical. This role will not be a 9-5, and the ideal candidate is excited about that.
Etched believes in the Bitter Lesson. We are the first inference-focused frontier AI system, betting early on transformer and transformer-like architectures and on increasing model sizes. Our addressable market is the entirety of inference, unlike many of our competitors.
We are a fully in-person team in San Jose (Santana Row), and greatly value engineering skills. We do not have boundaries between engineering and research, and we expect all of our technical staff to contribute to both and work across disciplines as needed.
Etched is building hardware for frontier intelligence. We co-design chips, racks, software, and manufacturing to deliver best-in-class throughput and latency across both prefill and decode workloads. Our first products are heavily focused on inference. Backed by hundreds of millions from top-tier investors and staffed by leading engineers, Etched is redefining the infrastructure layer for the fastest growing industry in history.
Purpose-built transformer ASICs for inference; 10x performance vs B200 at lower cost. Sohu targets hyperscalers' trillion-parameter deployments.
Series B · 100–200 people
FluidstackBuilds for teams inside the company
San Francisco, CAOn-site
$224,000–$300,000
$188,500–$282,700
OpenAIBuilds for teams inside the company
San Francisco, CAHybrid
$207,000–$385,000
$200,000–$250,000
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