Fellow Software Engineer — AI Performance & Reliability

KEY RESPONSIBILITIES:

PREFERRED EXPERIENCE:

ACADEMIC CREDENTIALS:

LOCATION:

• San Jose, CA or Bellevue, WA preferred (Hybrid). Other US locations may be considered.
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• Benefits offered are described: AMD benefits at a glance.
• 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.
• AMD may use Artificial Intelligence to help screen, assess or select applicants for this position. AMD’s “Responsible AI Policy” is available here.
• This posting is for an existing vacancy.

Qualifications

• Benefits offered are described: AMD benefits at a glance. 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. AMD may use Artificial Intelligence to help screen, assess or select applicants for this position. AMD’s “Responsible AI Policy” is available here. This posting is for an existing vacancy.

Responsibilities

• THE ROLE: We are looking for a strong, Principal or Fellow level software engineer to join our AI Infrastructure team. You will work on improving the performance, efficiency, and reliability of AI workloads across both model training and inference. Our team supports a broad range of machine learning systems, including large language models, diffusion models, and recommendation models. You will collaborate closely with customers and internal engineering teams to understand performance bottlenecks, optimize workloads, and ensure that models run reliably at scale. This role is a strong fit for an engineer who enjoys working across the AI software and hardware stack, solving technically challenging performance problems, and partnering directly with customers to make them successful. You will help customers achieve meaningful improvements in model performance and system reliability. You will identify difficult bottlenecks, develop reusable solutions, and help shape the infrastructure and product capabilities needed to run demanding AI workloads efficiently at scale. THE PERSON: - Profile and optimize AI model training and inference workloads. - Improve model throughput, latency, memory efficiency, scalability, and reliability. - Identify bottlenecks across models, frameworks, compilers, runtimes, operating systems, and hardware. - Optimize workloads involving large language models, diffusion models, recommendation systems, and other modern machine learning architectures. - Develop performance tooling, benchmarks, automation, and observability systems. - Investigate and resolve complex production issues affecting AI workloads. - Collaborate with customers to understand their technical requirements, reproduce issues, and recommend effective solutions. - Translate customer feedback into product and infrastructure improvements. - Work closely with machine learning engineers, systems engineers, hardware teams, and product teams.