Product & Yield Engineer (Data-focused)

Description

The company was founded in 2022 to build chips and systems that speed up AI inference, generating output at thousands of tokens per second while handling very long context lengths for large models.

Speed of inference is currently what limits progress on the hardest AI workloads, which already deliver value in drug discovery, software engineering, materials discovery and other fields built on deep reasoning.

The role supports development and manufacture of the company's silicon, focusing on product, yield and manufacturing data. It sits across New Product Introduction, Yield Engineering and Product Quality, analysing large semiconductor datasets to find trends, locate sources of variation, improve yield and reliability, and give clear technical conclusions to engineering teams and manufacturing partners. It is a hands-on individual contributor role for someone who likes working with data and turning analysis into engineering action.

Responsibilities

• Analyse large, complex semiconductor datasets to spot trends and isolate sources of variation.
• Work to improve yield and reliability across NPI, Yield Engineering and Product Quality.
• Explain technical findings clearly to engineering teams and manufacturing partners.

Requirements

• Proven semiconductor experience in Product Engineering, Test Engineering, Yield Engineering, Data Analytics or Quality Engineering, ideally from NPI through to high-volume production.
• Strong track record analysing manufacturing and test data to find trends, correlations, excursions, yield loss causes and improvement opportunities.
• Wide experience across as many of these areas as you can cover: wafer fab (process integration, yield enhancement, D0 control, defect reduction, process variation data); IC assembly (assembly process or package design, 3D IC and wafer stacking, assembly quality control, BOM optimisation, yield engineering); fabless work (IC product qualification, reliability and failure analysis, RMA investigation, production monitoring).
• Good working knowledge of WAT, WS/CP and FT datasets, including how results correlate across manufacturing and test stages.
• Strong data mining, statistical analysis and root-cause skills, with the ability to reach clear engineering conclusions from complex data.
• Experience spotting yield signatures, parameter distributions, outliers, spatial patterns, lot-to-lot variation, and systematic versus random failures.
• Extensive hands-on use of semiconductor data tools such as yieldHUB, Spotfire, JMP or equivalent.
• Ability to build scripts, automated analyses, dashboards and repeatable workflows for routine investigations and reporting.
• Practical use of statistical methods on manufacturing data, including SPC, Cp/Cpk, distributions, correlation analysis, hypothesis testing and trend analysis.
• Ability to combine data from several sources and manufacturing stages to investigate product and process problems.
• Familiarity with FMEA-based semiconductor qualification plans and standards such as JEDEC.
• Understanding of failure analysis methods and how analytical data guides the choice of destructive and non-destructive techniques.
• Ability to present findings concisely through visualisations, reports and technical presentations.
• Able to work independently on ambiguous problems, driving investigations from first data exploration to a supported conclusion.
• Good communicator who works well in a team.
• Self-starter who stays flexible and can run several analyses and investigations at once.
• Willing and able to travel worldwide when needed.
• Nice to have: experience building automated yield-monitoring, reporting or anomaly-detection workflows for semiconductors.
• Nice to have: experience with large semiconductor datasets using SQL, Python or similar tools.
• Nice to have: experience building dashboards, standard analysis journals or reusable engineering frameworks.
• Nice to have: experience working with Far East suppliers and manufacturing partners, and an awareness of multicultural working.
• Nice to have: a Bachelor's degree or higher in Electronics, Microelectronics, Semiconductor Physics, Engineering or a similar field.

Conditions

The company is UK-based and works on export-controlled technology under UK, US and other international rules; some roles may need extra eligibility checks, which will be explained during hiring.

The company is equal opportunity and works to build a diverse, inclusive team.

Benefits

• A competitive salary that reflects your experience and the specialist nature of the role.
• Meaningful equity so everyone shares in the value created.
• Private medical, dental and vision cover, a contributory pension, 25 days holiday plus bank holidays, and life and critical illness insurance.
• The company has recently raised $220M from investors including Founders Fund and Accel.