AI Solutions Architect – Production ML & GenAI

AMD

San Jose (CA)

On-site

USD 150,000 - 230,000

Full time

3 days ago
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Job summary

AMD is seeking an AI Software Development Engineer to architect, develop and accelerate scalable, production-ready AI/ML solutions across AMD's portfolio. You will define roadmaps, deliver PoCs, and support Tier 1 customers with reference solutions.

The role requires a BS/MS in CSE/EE, strong ML knowledge, and production software experience with CI/CD. Proficiency in Python/C/C++, deployment in Jupyter notebooks, and benchmarking on cloud platforms is essential. Onsite in San Jose, CA.

Qualifications

  • BS/MS in Computer Science, Computer Engineering, Electrical Engineering or related field.
  • Comprehensive knowledge of machine learning architectures, models and industry developer tools.
  • Prior work experience in developing production software solutions and CI/CD methods is critical.

Responsibilities

  • Develop and deliver machine learning solutions that demonstrate customer value across AMD's AI product portfolio.
  • Implementation and training of machine learning models in common frameworks, including fine-tuning models, and deployment on hardware systems.
  • Experience with deployed production runtime serving of machine learning applications.
  • Experience publishing to open source, including GitHub repositories and industry collaborations.
  • Experience emerging software frameworks for Generative AI and Agentic AI.

Skills

Python
C/C++
CI/CD
Machine learning
Jupyter notebooks
AWS
GCP
Azure

Education

BS/MS in Computer Science/Computer Engineering/Electrical Engineering

Tools

GitHub

Job description

AMD is seeking an AI Software Development Engineer to architect, develop and accelerate scalable, production-ready AI/ML solutions across AMD's portfolio. You will define roadmaps, deliver PoCs, and support Tier 1 customers with reference solutions.

The role requires a BS/MS in CSE/EE, strong ML knowledge, and production software experience with CI/CD. Proficiency in Python/C/C++, deployment in Jupyter notebooks, and benchmarking on cloud platforms is essential. Onsite in San Jose, CA.

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