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Fractile is a semiconductor hardware company founded in 2022, focused on building chips and systems optimized for efficient AI inference at scale. The company has raised $220M from top-tier investors including Founders Fund and Accel.
You will join as a Product & Yield Engineer with a data-focused specialization, playing a key role in the development and manufacture of Fractile's silicon products. Working across New Product Introduction (NPI), Yield Engineering, and Product Quality, you will analyze large and complex semiconductor datasets to identify trends, isolate sources of variation, improve yield and reliability, and provide clear technical insight to engineering teams and manufacturing partners. This is a highly hands-on individual contributor role for someone who enjoys working directly with data, investigating complex technical problems, and turning analysis into actionable engineering conclusions.
You will be responsible for analyzing semiconductor manufacturing and test data to identify yield loss mechanisms and opportunities for improvement. Your work will span wafer fab analysis (Process Integration, Yield Enhancement, D0 Control, defect reduction), IC Assembly (Assembly Process, Package Design, 3D IC and wafer stacking, Quality Control), and Fabless Semiconductor (Product Qualification, reliability and failure analysis, RMA investigation). You will create scripts, automated analyses, dashboards, and repeatable analytical workflows for standard engineering investigations and reporting. Strong communication skills are essential—you will present analytical findings through concise visualizations, reports, and technical presentations to both internal teams and external manufacturing partners.
The role offers competitive salary, meaningful equity, private medical/dental/vision, contributory pension, 25 days holiday plus bank holidays, and life/critical illness insurance. You will work in a diverse, collaborative environment solving some of the hardest problems in semiconductor engineering.
REQUIREMENTS:
- Demonstrable experience within the semiconductor industry in Product Engineering, Test Engineering, Yield Engineering, Data Analytics, or Quality Engineering, ideally spanning NPI through to high-volume production
- Strong experience analyzing semiconductor manufacturing and test data to identify trends, correlations, excursions, yield loss mechanisms, and opportunities for improvement
- Solid experience in wafer fab analysis (Process Integration, Yield Enhancement, D0 Control, defect reduction, process variation data), IC Assembly (Assembly Process, Package Design, 3D IC, wafer stacking, Quality Control, BOM optimization, Yield Engineering), and/or Fabless Semiconductor (IC Product Qualification, reliability and failure analysis, RMA investigation, production monitoring)
- Strong knowledge of WAT, WS/CP, and FT datasets, including correlation across manufacturing and test stages
- Excellent data mining, statistical analysis, and root-cause investigation skills
- Experience identifying yield signatures, parameter distributions, outliers, spatial patterns, lot-to-lot variation, and systematic versus random failure mechanisms
- Extensive hands-on use of semiconductor industry data analysis tools such as yieldHUB, Spotfire, JMP, or equivalent
- Ability to create scripts, automated analyses, dashboards, and repeatable analytical workflows
- Experience applying statistical methods to semiconductor manufacturing data (SPC, Cp/Cpk, distributions, correlation analysis, hypothesis testing, trend analysis)
- Ability to combine data from multiple sources and manufacturing stages to investigate complex product and process issues
- Familiarity with FMEA-derived semiconductor qualification plans and relevant standards such as JEDEC
- Understanding of semiconductor failure analysis methods and ability to use analytical data to guide investigation techniques
- Strong ability to communicate analytical findings through concise visualizations, reports, and technical presentations
- Comfortable working independently on ambiguous technical problems and driving investigations from initial data exploration through to a supported conclusion
- Good communication skills and collaborative, team-player attitude
- Self-starter, flexible, and able to manage multiple analyses and investigations in parallel
- Willing and able to travel worldwide when needed
DESIRABLE:
- Experience building automated semiconductor yield-monitoring, reporting, or anomaly-detection workflows
- Experience working with large semiconductor datasets using SQL, Python, or similar data-analysis tools
- Experience developing dashboards, standard analytical journals, or reusable engineering analysis frameworks
- Multi-cultural awareness, including experience working with Far East suppliers and manufacturing partners
- Bachelor's degree or above in Electronics, Microelectronics, Semiconductor Physics, Engineering, or similar discipline
