Jobs at Syntiant

The Digital Design Engineer will design digital systems for MEMS microphones, oversee digital architecture development, and verify digital systems. Requires collaboration with analog/mixed-signal designers and deep understanding of digital design flows.

Support product compliance and quality by evaluating materials and supplier declarations, researching international environmental and chemical regulations, preparing compliance disclosures and reports, assisting gap assessments and corrective actions, maintaining compliance databases, and participating in sustainability and product stewardship initiatives across cross-functional teams.

Lead a global Applications Engineering team supporting MEMS microphones and vibration sensors for edge AI products. Serve as primary technical resource for customers and sales, define sensor product roadmaps with Product and R&D, produce demos/reference designs/documentation, drive customer success, and collaborate cross-functionally. Travel up to 25%.

The Physical Design Engineer will drive the complete physical design flow for ASICs, ensuring top performance, power, and area while collaborating with cross-functional teams.

The Infrastructure and EDA Engineer will manage and maintain IT infrastructure, support EDA tools, and enhance operational procedures. Experience in EDA and IT infrastructure needed.

Responsible for designing digital systems for MEMS microphones, performing RTL design, supervising digital verification, and developing low-power architectures.

Design and integrate complex analog/mixed-signal ASICs for MEMS microphones and audio solutions. Lead block-level design and layout reviews, coordinate with digital/system teams, perform top-level mixed-signal simulations, and design/verify analog blocks to meet specifications.

The Staff Software Engineer will develop and support machine learning models for Syntiant Nural Decision Processors, collaborating with teams to convert models efficiently for real-world applications.

As a Principal Software Engineer, you will lead a team to develop model converter code for machine learning models, optimize performance, and work across the stack, including embedded firmware to support edge AI devices.