{"id":2909966,"url":"https://alion.io/job/amd-product-development-engineer","title":"Product Development Engineer","company":{"id":93,"name":"AMD","domain":"amd.com","url":"https://alion.io/company/amd","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Jibe","truth_index":{"grade":"B","score":75,"open_postings":162,"ghost_share":0,"stale_share":0.994,"repost_share":0,"time_to_fill_p50_days":29,"computed_at":"2026-10-25T05:49:26Z"}},"role":"Hardware","role_family":"Hardware","seniority":null,"employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Austin, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":118000,"max_usd":267000,"period":"year","method":"role_country_seniority_unknown","sample_n":2844},"experience_years_min":null,"visa_sponsorship":true,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Anomaly Detection","optional":false},{"name":"Machine Learning","optional":false},{"name":"NumPy","optional":true},{"name":"Python","optional":true},{"name":"Scikit-learn","optional":true},{"name":"SQL","optional":true},{"name":"Time Series","optional":true}],"status":"live","first_seen_at":"2026-10-15T17:03:00Z","employer_posted_date":"2026-10-20","last_verified_at":"2026-10-25T13:31:37Z","board_verified":true,"closed_at":null,"days_open":9,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":9},"description":"ADVANCE YOUR CAREER. ADVANCE THE WORLD.\nAt 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.\nWhether 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.\nTHE ROLE:\nThis is a critical role in improving quality and reliability of AMD’s industry-leading Server CPUs and Instinct accelerators. This role sits at the intersection of product engineering, test, yield, quality, and data science. You will work hands-on with massive volumes of manufacturing and test data, transforming them into actionable insights and production-ready analytics and machine-learning solutions. You will develop, deploy, and use tools for analyzing test and reliability data, deploy advanced analytics that reduce DPPM (defective parts per million), detect excursions earlier, and optimize test time and cost at scale. This is a highly cross-functional role where you will partner closely with Product Engineering, Test Engineering, Quality/Reliability, and Operations teams, influencing decisions from early ramp through high-volume manufacturing. The ideal candidate enjoys moving from exploration to deployment, and communicating results clearly to both technical teams and executive stakeholders.\nTHE PERSON:\nYou are a curious, analytical problem solver who thrives in complex, data-rich environments. You enjoy uncovering patterns in noisy data and translating them into practical improvements that matter in production. You collaborate naturally across functions, influence without authority, and are comfortable balancing deep technical work with clear communication. You are equally effective working independently or as part of a fast-paced, cross-disciplinary team, and you take pride in building robust, reusable solutions that scale.\nKEY RESPONSIBILITIES:\nPartner with Product Engineering, Test Engineering, Yield Engineering, Quality, and Operations to identify, define, and prioritize analytics and machine-learning use cases that materially improve yield, quality, and cost.\nDevelop and deploy ML/AI solutions for parametric outlier screening, drift detection, and excursion/anomaly detection across wafer, lot, site, and package dimensions.\nPerform in-depth root-cause analysis of yield loss and DPPM drivers by correlating test, fab, assembly, and design variables; distinguish systemic issues from statistical noise.\nBuild, productionize, and maintain yield and quality analytics within AMD’s AVA analytics platform, moving models from experimentation to scalable deployment.\nDrive adaptive test, screening, and binning strategies using data-driven insights to optimize product quality and manufacturing efficiency.\nAuthor clear technical documentation and reports; present findings and recommendations to cross-functional teams and executive audiences.\nContribute reusable code, analytics frameworks, and best practices that elevate team capability and accelerate future development.\nPREFERRED EXPERIENCE:\nStrong background in semiconductor product development, yield engineering, or test engineering, with hands-on experience analyzing high-volume manufacturing data.\nSolid foundations in statistics and machine learning, including hypothesis testing, DOE/RSM, regression, classification, outlier detection, time-series analysis, and anomaly detection.\nFamiliarity with Python and SQL for data analysis and modeling (e.g., pandas, NumPy, scikit-learn), general coding experience and demonstrated past ability in related scientific computing work.\nPractical knowledge of semiconductor manufacturing and test flows, including wafer sort and final test, binning strategies, DPPM analysis, reliability screens, and excursion management.\nFamiliarity with yield analytics ecosystems similar to AMD’s environment; experience with server-class CPUs and/or accelerator/GPU products is highly desirable.\nDemonstrated ability to deploy analytics or ML solutions into production environments, not just develop them in notebooks.\nACADEMIC CREDENTIALS:\nBachelor’s, Master’s, or Doctoral degree in Electrical Engineering, Computer Engineering, Computer Science, Physics, Applied Math, or a related technical discipline is preferred.\nThis role is not eligible for visa sponsorship.\n#LI-AP1\nBenefits offered are described: AMD benefits at a glance.\nAMD 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.\nAMD may use Artificial Intelligence to help screen, assess or select applicants for this position. AMD’s “Responsible AI Policy” is available here.\n\nThis posting is for an existing vacancy.\nTHE ROLE:\nThis is a critical role in improving quality and reliability of AMD’s industry-leading Server CPUs and Instinct accelerators. This role sits at the intersection of product engineering, test, yield, quality, and data science. You will work hands-on with massive volumes of manufacturing and test data, transforming them into actionable insights and production-ready analytics and machine-learning solutions. You will develop, deploy, and use tools for analyzing test and reliability data, deploy advanced analytics that reduce DPPM (defective parts per million), detect excursions earlier, and optimize test time and cost at scale. This is a highly cross-functional role where you will partner closely with Product Engineering, Test Engineering, Quality/Reliability, and Operations teams, influencing decisions from early ramp through high-volume manufacturing. The ideal candidate enjoys moving from exploration to deployment, and communicating results clearly to both technical teams and executive stakeholders.\nTHE PERSON:\nYou are a curious, analytical problem solver who thrives in complex, data-rich environments. You enjoy uncovering patterns in noisy data and translating them into practical improvements that matter in production. You collaborate naturally across functions, influence without authority, and are comfortable balancing deep technical work with clear communication. You are equally effective working independently or as part of a fast-paced, cross-disciplinary team, and you take pride in building robust, reusable solutions that scale.\nKEY RESPONSIBILITIES:\nPartner with Product Engineering, Test Engineering, Yield Engineering, Quality, and Operations to identify, define, and prioritize analytics and machine-learning use cases that materially improve yield, quality, and cost.\nDevelop and deploy ML/AI solutions for parametric outlier screening, drift detection, and excursion/anomaly detection across wafer, lot, site, and package dimensions.\nPerform in-depth root-cause analysis of yield loss and DPPM drivers by correlating test, fab, assembly, and design variables; distinguish systemic issues from statistical noise.\nBuild, productionize, and maintain yield and quality analytics within AMD’s AVA analytics platform, moving models from experimentation to scalable deployment.\nDrive adaptive test, screening, and binning strategies using data-driven insights to optimize product quality and manufacturing efficiency.\nAuthor clear technical documentation and reports; present findings and recommendations to cross-functional teams and executive audiences.\nContribute reusable code, analytics frameworks, and best practices that elevate team capability and accelerate future development.\nPREFERRED EXPERIENCE:\nStrong background in semiconductor product development, yield engineering, or test engineering, with hands-on experience analyzing high-volume manufacturing data.\nSolid foundations in statistics and machine learning, including hypothesis testing, DOE/RSM, regression, classification, outlier detection, time-series analysis, and anomaly detection.\nFamiliarity with Python and SQL for data analysis and modeling (e.g., pandas, NumPy, scikit-learn), general coding experience and demonstrated past ability in related scientific computing work.\nPractical knowledge of semiconductor manufacturing and test flows, including wafer sort and final test, binning strategies, DPPM analysis, reliability screens, and excursion management.\nFamiliarity with yield analytics ecosystems similar to AMD’s environment; experience with server-class CPUs and/or accelerator/GPU products is highly desirable.\nDemonstrated ability to deploy analytics or ML solutions into production environments, not just develop them in notebooks.\nACADEMIC CREDENTIALS:\nBachelor’s, Master’s, or Doctoral degree in Electrical Engineering, Computer Engineering, Computer Science, Physics, Applied Math, or a related technical discipline is preferred.\nThis role is not eligible for visa sponsorship.\n#LI-AP1\nBenefits offered are described: AMD benefits at a glance.\nAMD 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.\nAMD may use Artificial Intelligence to help screen, assess or select applicants for this position. AMD’s “Responsible AI Policy” is available here.\n\nThis posting is for an existing vacancy.","description_format":"text","description_chars":10492,"description_truncated":false,"requirements":{"experience_years_min":null,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"bachelor","optional":false},"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Processors, MCUs & AI Chips","Computer Components","AI Chips & Accelerators"],"lifecycle":[{"event":"open","at":"2026-10-20T09:19:33Z"}],"visa":[],"liveness":{"score":35,"band":"fade","label":"Fading","p_open":1,"p_active":0.352,"p_room":1,"age_days":9,"expected_fill_days":29,"reasons":["conf:0","stale_co","evergreen","velocity","win:early","comp:brand"],"computed_at":"2026-10-25T05:49:26Z"},"pay":null,"html_url":"https://alion.io/job/amd-product-development-engineer","json_url":"https://alion.io/job/amd-product-development-engineer.json","meta":{"generated_at":"2026-10-25T13:40:43Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","about":"Alion is a live layer of people, companies and AI agents: who they are, whether they are real and active right now, what they do and how to work with them, readable by people and by agents and paid per call.","catalog":"https://alion.io/catalog.json","usage":{"tier":"crawler_verified","counted_by":"address","units_charged":1,"used_today":19494,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-10-26T00:00:00Z"}},"offers":[{"id":"company.slices","title":"One company in depth, by slice","status":"live","price":{"credits":0.02,"usd":0.002,"plus_per_slice":{"credits":0.05,"usd":0.005}},"unit":"per company, plus each slice with data","note":"the employer in depth","call":{"mcp_tool":"get_company","arguments":{"id":93},"rest":"https://alion.io/mcp/rest/get_company?id=93"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Famd-product-development-engineer"},{"id":"market.stats","title":"A market slice: pay, demand and time to fill","status":"live","price":{"credits":1,"usd":0.1},"unit":"per slice","note":"pay, demand and time to fill for this role and place","call":{"mcp_tool":"market_stats"},"human":"https://alion.io/catalog?offer=market.stats&for=job%2Famd-product-development-engineer"},{"id":"job.search","title":"Open jobs by role, technology, place, pay and visa","status":"live","price":{"credits":0.02,"usd":0.002},"unit":"per posting in a list","note":"similar open postings","call":{"mcp_tool":"search_jobs"},"human":"https://alion.io/catalog?offer=job.search&for=job%2Famd-product-development-engineer"},{"id":"company.verify","title":"Is this company real and active right now","status":"pilot","price":null,"unit":"per company","request":{"url":"https://alion.io/catalog/request","method":"POST","body":"{\"offer\": \"company.verify\", \"for\": \"job/amd-product-development-engineer\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Famd-product-development-engineer"}]}