Member of Staff

Wafer; San Francisco (CA); On-site; USD 180,000 - 260,000; Full time

Benefits offered by this job

Fully covered medical, dental, and vis

Lunch and dinner, unlimited PTO, and p

Housing stipend $1K/month (post-tax)

Uber/Waymo from/to office

Visa sponsorship available

Job summary

Wafer is building AI systems to optimize inference workloads across silicon. We seek a candidate who understands compute deeply, connects technical details to economics, and can explain from GPU architecture to contracts and financial models.

Join a team that collaborates with engineering, finance, and suppliers to drive capacity decisions, negotiate terms, and ensure deliverables meet budgets and performance targets.

Qualifications

• Understand compute beyond the spec sheet.
• Exceptional with numbers; build a financial model and explain profit vs cash.
• 1-5 years of relevant experience; compute infrastructure, semiconductors, finance or investing is valuable.
• Credible with engineers and commercially sharp with suppliers.
• Able to work without a fully defined spec and deliver concrete answers.

Responsibilities

• Work with engineering and finance to understand models and hardware configurations profitability.
• Build models connecting inference performance, utilization, pricing, compute costs and cash requirements.
• Evaluate GPU supply and supplier proposals; compare price, availability, contract length, deposits, reliability and flexibility.
• Help source and negotiate capacity, then track delivery and performance against agreements.
• Turn changing demand and hardware economics into concrete capacity decisions.
• Investigate discrepancies across usage, invoices and contracts, and build reliable systems.

Skills

Compute economics

Numerical ability

Experience: 1-5 years

Compute infra background

Semiconductors background

Finance background

Supplier relationships

Problem solving without specs

Job description

Member of Staff

At Wafer, we are building AI systems that automatically optimize inference workloads across silicon. Turning better performance into a better business takes more than faster software. We need the right compute, on the right terms, serving the right demand.

We're looking for someone who understands compute deeply and can connect the technical details to the economics. You should be able to go from GPU architecture to a supplier contract to a financial model, and explain what we should do.

What you'll do

• Work with engineering and finance to understand which models and hardware configurations make money, and what changes that.

• Build models connecting inference performance, utilization, pricing, compute costs and cash requirements.

• Evaluate GPU supply and supplier proposals. Compare price, availability, contract length, deposits, reliability and flexibility.

• Help source and negotiate capacity, then track whether delivery and performance match what we agreed.

• Turn changing demand and hardware economics into concrete capacity decisions.

• Investigate discrepancies across usage, invoices and contracts, and build systems that keep those numbers reliable.

What we look for

• You understand compute beyond the spec sheet. You can explain how GPU architecture, memory, networking and software affect the cost of serving a real workload.

• You are exceptional with numbers. You can build a clear financial model, challenge its assumptions and explain the difference between profit and cash.

• You have roughly 1-5 years of relevant experience. A background in compute infrastructure, semiconductors, finance or investing is valuable. What matters most is evidence that you can do this work exceptionally well.

• You are credible with engineers and commercially sharp with suppliers. You ask precise questions and follow the details through to a decision.

• You work without a spec. You can take a half-defined problem, find the information that matters and come back with a concrete answer.

How we evaluate

We score every candidate on seven values:

1. Infinitely Resourceful

2. Exceptionalism

3. Unreasonable Standards

4. Company Over Self

5. High EQ

6. Learns Quickly

7. First Principles Thinker

Benefits

• Fully covered medical, dental, and vision insurance.

• Daily lunch and dinner, unlimited PTO, and parental leave.

• $1K/month housing stipend (post-tax) if you live within walking distance (0.5 miles) from the office.

• Covered Uber/Waymo from/to office.

• Visa sponsorship available.

How we work

On-site in San Francisco, five days a week. Small team with massive surface area and ownership. You operate with complete autonomy of how to solve problems.

You will work directly with engineering, finance and suppliers. Your work should end in better decisions about the compute we run, what it costs and how we scale.