Physical AI, Machine Learning Engineer

Amd

Confirmed live yesterday High trust
Hybrid

Quick summary

Work type
Hybrid
Location
San Jose, CANovi, MIAustin, TX
Salary
$204,000–$306,000 / yr
Posted
86 days ago
Freshness
Confirmed live yesterday
Closes
Jun 17, 2027

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $206k
This role $255k
$132k most similar roles pay here $325k

This role pays more than 85% of similar roles. Most pay $165,000–$247,503 — the shaded band above. At the midpoint, this role pays about $255k versus about $206k for comparable roles.

Based on 240 similar postings.

Employer

About Amd

AMD (Advanced Micro Devices) is a semiconductor company that develops high-performance processors, graphics cards, and adaptive computing solutions for gaming, data centers, and embedded markets. Industry: Semiconductors

Amd currently has 367 open roles on FindRole.

Listed pay typically runs $166,400–$249,600 across 367 roles with salary data.

Most-posted roles

View all roles at Amd

At a glance

TL;DR · Physical AI, Machine Learning Engineer

As a Senior Physical AI Software Engineer on the Physical AI team, you will develop next-generation software for intelligent edge systems that integrate embedded computing, real-time processing, computer vision, and artificial intelligence. You will design and optimize software across heterogeneous architectures including CPUs, GPUs, FPGAs, and dedicated AI accelerators to enable machines to perceive and respond to their environments with low-latency performance. Your daily work involves building software for Linux and RTOS platforms, developing sensor processing pipelines, and integrating AI inference applications. Key technical requirements include experience with Vitis AI, Versal AI Edge, Zynq UltraScale+, Kria, and frameworks like PyTorch or TensorFlow. You will also utilize ROS 2, ONNX, and graphics technologies like Vulkan to solve complex problems in robotics, industrial automation, automotive systems, and aerospace applications within the physical AI domain.

What does a Machine Learning Engineer earn in California?

Median $246394 from 172 postings across 28 companies.

See salary data

What you'll do

  • Design, develop, and maintain embedded software for AI-enabled edge computing platforms.
  • Develop software for Linux and Real-Time Operating Systems (RTOS) to ensure deterministic, low-latency execution.
  • Implement real-time software for perception, sensor processing, control, and autonomous decision-making.
  • Integrate computer vision, image processing, and AI inference applications for real-world deployment.
  • Build and optimize high-performance pipelines for image, video, and sensor data.
  • Optimize software across heterogeneous computing architectures including CPUs, GPUs, FPGAs, and AI accelerators.
  • Perform platform bring-up, debugging, validation, and system integration.
  • Analyze and optimize system performance regarding latency, throughput, memory usage, and power efficiency.

What we're looking for

  • Experience developing software for embedded Linux and Real-Time Operating Systems (RTOS).
  • Expertise in designing real-time software for perception, sensor processing, and autonomous decision-making.
  • Proficiency in optimizing software across heterogeneous computing architectures including CPUs, GPUs, FPGAs, and AI accelerators.
  • Experience integrating computer vision, image processing, and AI inference applications for real-world deployment.
  • Familiarity with AI frameworks such as ONNX, PyTorch, or TensorFlow and model optimization techniques like quantization and pruning.
  • Experience with ROS 2 and robotics software architectures.
  • Knowledge of perception systems including camera, radar, lidar, and sensor fusion pipelines.
  • Experience with low-level platform software development, including Linux kernel and device drivers.

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