Build Ai
ML Engineer, Inference Optimization
San Francisco, California, United States · On-site · FullTime
USD 200,000–320,000/year
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About the role
Description from the employer’s posting. Check the employer’s page for the current version.
- EmployerBuild Ai
- LocationSan Francisco, California, United States
- Work styleOn-site
- Employment typeFullTime
- Employer posted
- Salary (as stated by the employer)USD 200,000 – 320,000 per year
About Build AI
Build AI is the data hyperscaler for Physical AI. We're vertically integrated across hardware, manufacturing, logistics, collection, and model training to scale the physical labor dataset orders of magnitude faster than anyone in the world.
Job Summary
Inference is about 90% of compute spend. Economics are heavily driven by inference optimization. We’re hiring someone to make inference cheaper, faster, and good enough that we can scale the data engine and the product without the GPU bill eating the company.
Key Responsibilities
Own inference performance: latency, throughput, and cost per unit of work (tokens, frames, or jobs)
Cut the 90% compute line: kernels, batching, quantization, compilation, serving, and hardware utilization
Profile pipelines (Nsight, PyTorch Profiler, or equivalent), find the real bottleneck, and ship the fix
Show full description
Work with research and product so models that are accurate are also affordable to run at scale
Build the serving and eval path so experiments don’t hide the inference bill
Measure cost as a first-class metric, not an afterthought once quality is “done”
You may be a good fit if you have (Must-have qualifications)
Strong ML / systems engineer with real inference optimization experience (serving, compilers, CUDA/kernels, quantization, or similar)
Comfortable in Python and in C++ or Rust for performance-critical paths
You think in dollars and tokens/frames per second, not only in accuracy tables
Familiarity with PyTorch (or JAX) and with profiling tools
Comfortable in a small research team shipping under cost pressure
Strong candidates may also have experience with (Nice-to-have qualifications)
CUDA, kernels, compilers (TVM, MLIR, TensorRT), or quantization in production
You have owned GPU/accelerator cost as a first-class metric
Serving stacks for video or large models
Understanding of memory hierarchy, data movement, and low-precision compute
Benefits
Competitive pay
Medical, dental, and vision packages with generous premium coverage
$500 per month credit for waiving medical benefits
Housing subsidy of $2k per month for those living within walking distance of the office
Relocation support for those moving to San Francisco (Financial District) or Shenzhen (Nanshan)
Various wellness benefits covering fitness, mental health, and more
Daily lunch and dinner in our office
Unlimited compute budget subject to ROI justification
Unlimited Codex and Claude credits
Travel
How we're different
Build believes in the Bitter Lesson. By taking a general approach of learning from humans, our addressable market is all physical labor.
We are a fully in-person team in San Francisco (Financial District) and Shenzhen (Nanshan), 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.
Build AI is an equal opportunity employer. We review every application. If you do not meet every bullet, still apply. Questions: research@build.ai
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- USD a year, after annualising120,000–400,000 (11 listings, 8 employers)
At a glance
- Work styleOn-site
- Employment typeFullTime
- Salary (as stated by the employer)USD 200,000–320,000 per year
- Employer posted
- Added to ROLIVA
- Last checked
Skills in this posting
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