AMD

AI Models MAD - Model Automation and Dashboarding

AMD · Austin, TX

  • On site
  • Full-time
  • $130,000 / year
  • Austin, TX

Job highlights

  • Automate AI model testing on AMD hardware.
  • Develop tools for benchmarking and regression tracking.
  • Build performance dashboards and metrics for users.
  • Collaborate on AI models and open-source contributions.
  • Ensure ROCm client confidence through validation.

About the role

AI Models MAD - Model Automation and Dashboarding Software Engineer

At AMD, our mission is to build great products that accelerate next-generation computing experiences—from AI and data centers, to PCs, gaming and embedded systems. Grounded in a culture of innovation and collaboration, we believe real progress comes from bold ideas, human ingenuity and a shared passion to create something extraordinary. When you join AMD, you’ll discover the real differentiator is our culture. We push the limits of innovation to solve the world’s most important challenges—striving for execution excellence, while being direct, humble, collaborative, and inclusive of diverse perspectives. Join us as we shape the future of AI and beyond. Together, we advance your career.

The Role

AMD is looking for a skilled and motivated software engineer to join the Model Automation and Dashboarding (Framework MAD) team — a group focused on ensuring the reliability, performance, and scalability of AI models running on AMD hardware. As part of this team, you’ll build and maintain tools and infrastructure that automate functional and performance validation of deep learning models across ROCm and GPU platforms. Your contributions will directly impact developer confidence, model portability, and transparent benchmarking for internal teams and the open-source community.

The Person

We are seeking a software developer with strong technical expertise in Python and Linux-based systems, who is passionate about quality assurance, benchmarking, and automation in the AI/ML space. The ideal candidate thrives in both collaborative and independent environments, demonstrates excellent problem-solving skills, and takes ownership in defining goals and delivering impactful solutions. Experience working with machine learning frameworks, performance dashboards, or automation platforms is a strong plus.

Key Responsibilities

  • Model Testing & Validation: Automate functional and performance testing of AI models across ROCm-supported hardware using scalable tools and pipelines.
  • Software Engineering Excellence: Proficiency in Python and C++ with deep experience in performance tuning, debugging, and robust test design, ensuring reliable, maintainable, high-performance codebases.
  • Benchmarking Infrastructure: Develop tools for continuous benchmarking and regression tracking across hardware generations and ROCm releases.
  • Dashboard & Metrics Development: Build and maintain real-time dashboards that report relevant performance, accuracy, and reliability metrics for both internal and public users.
  • Ecosystem Integration: Collaborate with teams like Deep Learning Models (DLM) and MADengine to support a wide range of models, including public and private/NDA workloads.
  • Client Enablement: Ensure out-of-box confidence for ROCm clients by validating model performance and functionality in standardized and reproducible environments.
  • Scalable Tooling: Contribute to the design of portable, easy-to-use Python interfaces that support multi-node profiling, distributed workloads, and containerized deployments.
  • Open-Source Contributions: Support public-facing MAD GitHub repositories and Docker releases, enabling the community to run and validate models on ROCm.

PREFERRED EXPERIENCE

  • Programming & Tooling: Strong Python development skills, with experience in test automation, CI/CD, and Linux scripting.
  • Machine Learning Workflow Understanding: Familiarity with AI frameworks (e.g., PyTorch, TensorFlow), model benchmarking, and ML model lifecycles.
  • Performance Analysis: Strong experience with profiling tools, system monitoring, or regression tracking systems for deep learning models.
  • DevOps & Dashboards: Solid experience in performance dashboards, visualization tools (e.g., Grafana, Plotly), and metrics collection pipelines.
  • Software Engineering Practices: Proficiency with version control (GitHub), testing strategies, code reviews, and collaborative software development.
  • Communication & Ownership: Strong written and verbal communication skills with a proactive approach to defining and driving development efforts.

ACADEMIC CREDENTIALS

Undergraduate and/or Master’s Degree in Computer Science, Computer Engineering, Electrical Engineering, or a related field.

Benefits

Benefits offered are described: AMD benefits at a glance.

Equal Opportunity Employer

AMD does not accept unsolicited resumes from headhunters, recruitment agencies, or fee-based recruitment services. AMD and its subsidiaries are equal opportunity, inclusive employers and will consider all applicants without regard to age, ancestry, color, marital status, medical condition, mental or physical disability, national origin, race, religion, political and/or third-party affiliation, sex, pregnancy, sexual orientation, gender identity, military or veteran status, or any other characteristic protected by law. We encourage applications from all qualified candidates and will accommodate applicants’ needs under the respective laws throughout all stages of the recruitment and selection process.

AI in Hiring

AMD may use Artificial Intelligence to help screen, assess or select applicants for this position. AMD’s “Responsible AI Policy” is available here.

Vacancy Status

This posting is for an existing vacancy.

Key skills/competency

  • Python
  • Linux
  • AI/ML
  • Automation
  • Testing
  • Benchmarking
  • CI/CD
  • Deep Learning
  • Performance Tuning
  • Software Engineering

Skills & topics

  • AI Models
  • Model Automation
  • Dashboarding
  • Software Engineer
  • Python
  • Linux
  • AI/ML
  • Automation
  • Testing
  • Benchmarking
  • ROCm
  • GPU
  • Deep Learning
  • CI/CD
  • Performance Tuning
  • Open Source
  • GitHub
  • Docker
  • Grafana
  • Plotly
  • AMD

How to get hired

  • Tailor your resume: Highlight Python, Linux, AI/ML, automation, and benchmarking experience.
  • Showcase projects: Detail your contributions to CI/CD, performance analysis, or dashboard development.
  • Prepare for technical interviews: Brush up on Python coding, Linux commands, and AI/ML concepts.
  • Demonstrate problem-solving: Be ready to discuss how you approach complex technical challenges.
  • Research AMD's culture: Align your answers with their values of innovation and collaboration.

Technical preparation

Master Python for automation and scripting tasks.,Deepen knowledge of Linux environments and commands.,Familiarize with PyTorch, TensorFlow, and model lifecycles.,Practice performance profiling and system monitoring.

Behavioral questions

Describe a complex automation challenge you solved.,How do you ensure code quality and reliability?,Share an experience of collaborating on a technical project.,How do you prioritize tasks and manage your time?

Frequently asked questions

What are the key technical skills required for the AI Models MAD role at AMD?
The AI Models MAD role at AMD requires strong technical expertise in Python and Linux-based systems. Experience with AI frameworks (PyTorch, TensorFlow), test automation, CI/CD, performance analysis tools, and visualization platforms like Grafana or Plotly is highly valued. Proficiency in C++ and understanding of software engineering practices such as version control (GitHub) and code reviews are also important.
What is the primary focus of the Model Automation and Dashboarding team at AMD?
The primary focus of the Model Automation and Dashboarding (Framework MAD) team at AMD is to ensure the reliability, performance, and scalability of AI models running on AMD hardware. This involves building and maintaining tools and infrastructure for automated functional and performance validation of deep learning models across ROCm and GPU platforms.
What kind of contributions will I make as an AI Models MAD Software Engineer at AMD?
As an AI Models MAD Software Engineer at AMD, you will automate functional and performance testing of AI models, develop benchmarking infrastructure, build real-time performance dashboards, and contribute to scalable tooling. You will also integrate with other teams and support open-source contributions to the MAD GitHub repositories and Docker releases.
Does AMD use AI in its hiring process for the AI Models MAD position?
Yes, AMD may utilize Artificial Intelligence to assist in screening, assessing, or selecting applicants for this position. You can find more information regarding their approach in AMD’s “Responsible AI Policy”.
What academic background is preferred for this Software Engineer role at AMD?
AMD prefers candidates with an Undergraduate and/or Master’s Degree in Computer Science, Computer Engineering, Electrical Engineering, or a closely related technical field for this Software Engineer role.
How can I highlight my suitability for the AI Models MAD role during the application process?
To highlight your suitability for the AI Models MAD role, emphasize your Python and Linux proficiency, experience with AI/ML frameworks and automation, and any background in performance analysis or dashboard development. Showcase your contributions to collaborative projects and your understanding of software engineering best practices.
AI Models MAD - Model Automation and Dashboarding at AMD | Apply at AMD | Jobs near Austin | PitchMeAI