Skip to content
CV Rocket
Get started
How it worksThe enginePricingBlogContactSign in

Open nowPosted 121 days ago

Staff AI Inference and Acceleration Engineer

Figure AI104 open roles

Pay
$180,000 – $275,000 a year
Where
San Jose, CA
Get the CV for this job

From $25 per CV, paid once. No subscription.

Your applicationOpen nowStaff AI Inference and Acceleration EngineerFigure AI · San Jose, CA

  1. YouYes, apply to this one.

  2. CV RocketCV written for this posting.

  3. 25 readersRecruiter, hiring manager, skeptic. Round after round.

  4. CV RocketApplied on Figure AI's own form.

The reply lands in your private mailbox

3×more interviews than doing it yourself with ChatGPT.

The clock on this job

Early applications get read.

12.3% of postings close within 7 days. Measured by our own scanner across the market. Figure AI postings stay open a median of 52 days.

Share of postings closed within
  1. 2.1%1 day
  2. 4.5%3 days
  3. 12.3%7 days
  4. 19.3%14 days
  5. 35.6%30 days
  6. 57.8%60 days
This job: posted 121 days ago

Figure AI median: 52 days open

The posting

Figure is an AI robotics company developing autonomous general-purpose humanoid robots. The goal of the company is to ship humanoid robots with human level intelligence. Its robots are engineered to perform a variety of tasks in the home and commercial markets. Figure is headquartered in San Jose, CA.

We are looking for a Staff AI Inference & Acceleration Engineer to join the Platform Software team and own the on-board inference architecture for Figure’s humanoid robots. You will be the technical authority on how AI workloads are mapped, optimized, and executed across the robot’s compute hardware — driving down power consumption and cost while meeting the strict latency and reliability demands of a real-time autonomous system.

Responsibilities:

  • Own the on-board inference architecture — mapping models to available accelerators (NPU, GPU, DSP, CPU) based on latency, power, and memory budgets.
  • Partition inference workloads across heterogeneous compute resources, balancing real-time performance with power and thermal constraints.
  • Define and maintain a system-level compute budget across all inference tasks running on the robot.
  • Evaluate next-generation acceleration hardware and contribute to the definition of future compute platform requirements.
  • Optimize inference toolchains end-to-end — from model export through runtime execution — for target hardware.
  • Apply quantization (INT8, INT4, mixed-precision), pruning, operator fusion, and other compression techniques to reduce compute, memory, and power footprint.
  • Profile inference pipelines to identify and eliminate bottlenecks in latency, memory bandwidth, and power consumption.
  • Optimize kernel scheduling, memory layout, and data movement across the compute hierarchy.
  • Partner closely with the AI/ML team to define model architecture constraints that are hardware-friendly from the outset.
  • Work with the Platform Software team on runtime integration, scheduling, and power management.
  • Engage with silicon vendors and research teams to track the accelerator landscape and influence hardware roadmaps.

Requirements:

  • M.S. or Ph.D. in Computer Engineering, Electrical Engineering, Computer Science, or a related field — or equivalent industry experience.
  • At least 8 years of industry experience in hardware acceleration, ML systems, or compute architecture.
  • Deep understanding of AI/ML inference — model formats (ONNX, TFLite, etc.), inference runtimes, and deployment pipelines.
  • Hands-on experience optimizing models for edge or embedded hardware using quantization, pruning, and operator-level tuning.
  • Strong understanding of computer architecture — memory hierarchies, data movement, and heterogeneous compute.
  • Experience profiling and benchmarking inference workloads across CPU, GPU, NPU, DSP.
  • Familiarity with low-level toolchains and compilation frameworks (e.g. TVM, MLIR, TensorRT, Torch, SNPE/QNN, JAX, CUDA, ROCm).
  • Solid software engineering skills in C++ and Python.
  • Strong cross-functional communication skills — able to work effectively across hardware, software, and AI/ML teams.

Bonus Qualifications:

  • Knowledge of real-time operating constraints and their impact on inference scheduling.
  • Track record of co-designing model architectures with ML teams to meet hardware constraints.

The US base salary range for this full-time position is $180,000 to $275,000 per year.

The pay offered for this position may vary based on several individual factors, including job-related knowledge, skills, and experience. The total compensation package may also include additional components/benefits depending on the specific role. This information will be shared if an employment offer is extended.

From $25, paid onceGet the CV for this job

What happens when you press

One press. We do the rest.

  1. A CV for this posting

    Written against Figure AI's own wording, from every piece of relevant proof in your profile.

  2. 25 readers review it

    Recruiter, hiring manager, skeptic and more read every draft, round after round. You get the best round.

    The review screen in CV Rocket: how each CV was read, round by round.

  3. We apply on Figure AI's form

    Our application engine gets through the hardest forms there are. Where a question needs you, AI suggests the best answer. Don't want us applying from our IP addresses? Use our Chrome extension: we apply straight from your own browser.

    An application in CV Rocket: every answer filled in on the employer's form.

  4. Every reply, sorted

    Figure AI's answer lands in your private mailbox, and we classify it on arrival: interview, question, rejection.

    The CV Rocket inbox: each employer reply classified as an interview, an action or a rejection.

  5. Reply with AI

    AI helps you write the email, checks it and sends it. We show you whether the recruiter read it.

  6. The interview in your calendar

    Full integration with your calendar. The invitation goes straight in.

    An interview invitation in the CV Rocket inbox, added to the candidate's calendar.
Get the CV for this job

From $25 per CV, paid once. No subscription.

Why it works

3×

more interviews than doing it yourself with ChatGPT.

ChatGPT writes a CV and never learns what happened to it. We see every reply. For each CV we know:

  • How it was written, and how the review scored it
  • When we applied, and how long after the posting went up
  • Which posting, which company, which city
  • Who got the interview, and who heard nothing

That is how we know which CVs get called.

Get the CV for this job

From $25 per CV, paid once. No subscription.

The numbers game

More applications. More interviews.

Every application goes out with its own CV, written for that posting and paid once. Send enough of them and the law of large numbers finds you the job.

Get the CV for this job
By hand5–10
With CV Rocket100
applications a day

Nearby

Live postings like this one

Same employer first, then the same role elsewhere.

Before you press

Straight answers

Get the CV for this job

From $25 per CV, paid once. No subscription.

What if my background isn't good enough?

We make the most of the background you have. The CV uses every piece of relevant proof your profile holds, and one of the 25 readers reads your whole profile and flags what the CV left out.

Do you really apply for me?

Yes, on the employer's own form, the hardest ones included. Where a question needs you, you answer it right there and AI suggests the best answer. Don't want us applying from our IP addresses? Use our Chrome extension: we apply straight from your own browser.

Is it a subscription?

No. You pay once per CV, from $25. Every application goes out with its own CV, written for that posting.

One job. One CV.
Paid once.

Pick the posting you want. We write for it, apply for you and catch the reply.

Get the CV for this job

From $25 per CV, paid once. No subscription.