Data Architect for High Speed I/O (HSIO) Validation

WHAT YOU DO AT AMD CHANGES EVERYTHING We care deeply about transforming lives with AMD technology to enrich our industry, our communities, and the world. Our mission is to build great products that accelerate next-generation computing experiences – the building blocks for the data center, artificial intelligence, PCs, gaming and embedded. Underpinning our mission is the AMD culture. We push the limits of innovation to solve the world’s most important challenges. We strive for execution excellence while being direct, humble, collaborative, and inclusive of diverse perspectives. AMD together we advance_ THE ROLE: The AI and HPC market is expanding rapidly, demanding higher I/O performance and complex system topology cases. Our DCGPU (Data Center GPU) products demand higher levels of quality and reliability in production. We are searching for a Data Architect to help drive our volume data strategy and integration into validation flows. This includes data collection and predictive modelling of quality metrics in manufacturing for high speed SerDes I/O like PCIe 5/6.   THE PERSON: You will be a part of a team driving to improve AMD's product quality. You will be applying your Data Architecture experience to tackle challenging volume validation, manufacturing, and issue debug problems.   KEY RESPONSIBILITIES: Drive automation and data strategy with validation technical leads to reduce time to market and time to quality for future products Develop database solutions to support storage and analysis of test results from validation and manufacturing Develop Python scripts for performance metrics data collection and characterization Deliver robust data analytics solutions for visualization, results reporting, and building predictive statistical models  PREFERRED EXPERIENCE 10+ years' experience in designing high-availability, low-latency enterprise solutions as a Data Architect or Data Science/Engineering subject matter expert Knowledge of data modelling and data warehouse/lake best practices (SQL, Snowflake) Experience with data analytics, visualizations, and report generation (PowerBI, JMP) Experience building statistical predictive models factoring multiple sources of variation in chip and system manufacturing Experience writing performant code in Python, Java, Scala and good experience with Spark Enforcing and applying best practices for modular code development including 3rd party tool integration Experience with SerDes PHY or High Speed I/O Validation at PCIe Gen5 or 6 speeds, and above HSIO lane margining characterization for PHY, PCB Channel, and system designs Linux power user ACADEMIC CREDENTIALS: Bachelors or Master’s degree in Computer Engineering, Electrical Engineering, or Computer Science   LOCATION: Austin, TX #LI-SL2 #LI-HYBRID At AMD, your base pay is one part of your total rewards package. Your base pay will depend on where your skills, qualifications, experience, and location fit into the hiring range for the position. You may be eligible for incentives based upon your role such as either an annual bonus or sales incentive. Many AMD employees have the opportunity to own shares of AMD stock, as well as a discount when purchasing AMD stock if voluntarily participating in AMD’s Employee Stock Purchase Plan. You’ll also be eligible for competitive benefits described in more detail here. 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.