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At AMD, we believe technology has the power to solve the world’s most important challenges. From advancing healthcare and scientific discovery to powering AI and the technologies people rely on every day, innovation at AMD is shaping the future.
Whether you’re designing next-gen processors, enabling AI breakthroughs, or bringing leading edge products to market, every role at AMD contributes to something bigger — technology that moves the world forward. Join us and, together, we’ll advance your career.
THE ROLE:
We are seeking a hands-on engineer to build and operate the development infrastructure and AI solutions that underpin AMD's AI-assisted silicon design program. This role sits at the intersection of ASIC design methodology, developer infrastructure, and AI/ML engineering, and is responsible for making AI capabilities dependable, measurable, and genuinely usable within production hardware development flows.
This is a unique opportunity that combines silicon development methodologies with AI and machine learning solution development. The successful candidate will join a team at the forefront of developing AI solutions and driving adoption across AMD's hardware development organizations.
In this role, you will modernize how design and verification teams build, version, and release their work through improvements in source control platforms, code management systems, continuous integration and delivery (CI/CD), compute and storage infrastructure, and the governance controls required for production silicon development. You will also build the instrumentation, telemetry, and benchmarking frameworks used to quantify AI solution performance and business impact.
Working closely with RTL designers, verification engineers, and CAD teams, you will translate hardware development methodologies into scalable AI-enabled solutions that integrate seamlessly into real silicon development workflows.
THE PERSON:
The ideal candidate is a pragmatic engineer with a strong systems mindset and data-driven approach. You believe that what is not measured cannot be improved and are equally comfortable working within a hardware team's development environment and the data pipelines that explain its performance.
You bring deep infrastructure engineering expertise, along with sufficient understanding of ASIC design and RTL development processes to build solutions that hardware engineers trust and adopt. You are rigorous about reliability, auditability, and operational efficiency, and you treat shared infrastructure as a product with real users rather than as a support function.
You establish credibility quickly with engineering teams by understanding the rigor and schedule demands of silicon development and by translating emerging AI capabilities into dependable, production-ready engineering solutions.
KEY RESPONSIBILITIES:
- Modernize source control, code management, and release workflows for design and verification teams, including repository architecture, large-file and IP management, branching strategies, and CI/CD implementation.
- Build and operate the compute and storage infrastructure that supports AI services and AI asset management.
- Develop instrumentation and telemetry frameworks for AI solutions, including usage tracking, cost attribution, performance monitoring, and workflow analytics.
- Establish benchmarking and evaluation methodologies that quantify AI solution quality, productivity impact, throughput, and cost efficiency.
- Partner with RTL, verification, and CAD teams to understand development methodologies and translate them into AI-enabled engineering workflows.
- Drive AI solution adoption through onboarding, documentation, training, and user support across IP, SoC, and platform development teams.
PREFERRED EXPERIENCE:
- Strong software engineering skills in Python; C++ or similar languages are a plus, with experience building production services, APIs, automation solutions, and CI/CD pipelines.
- Hands-on expertise with Git, GitHub, or equivalent enterprise source control platforms, including large-scale repository management and migration efforts.
- Working knowledge of ASIC development flows, including RTL design using Verilog/SystemVerilog, verification methodologies, regression environments, and EDA tool ecosystems.
- Experience with EDA compute environments, including LSF, Slurm, distributed storage systems, and Linux infrastructure at scale.
- Experience with telemetry systems, time-series data pipelines, dashboarding and visualization tools (e.g., Power BI), and statistical analysis.
- Familiarity with LLM operations, model evaluation, usage and cost accounting, AI service deployment, and benchmarking methodologies.
- Demonstrated success leading platform rollouts or enterprise-scale shared service adoption initiatives.
- Excellent communication, collaboration, and stakeholder management skills.
ACADEMIC CREDENTIALS:
- Bachelor's or Master's degree in Computer Engineering, Electrical Engineering, Computer Science, or a related technical discipline.
LOCATION:
#LI-MO2
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.