ML Engineer, Inference Optimization

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

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: [email protected]