Job description

About Unconventional Since 2022, AI has entered the mainstream, reshaping entire industries from education and software development to fundamental consumer behaviors. This revolution has created an unprecedented demand for computation - a demand that is now fundamentally limited by energy, not just in the datacenter, but at a global scale. At Unconventional, our mission is to solve this. We are rethinking computing from the ground up to build a new foundation for AI that is 1000x more efficient. We're doing this by exploiting the rich physics of semiconductors, mapping neural networks directly to the device physics rather than relying on layers of inefficient abstraction. The Role As a Member of Technical Staff, Silicon Validation Engineer, you will be a foundational member of our small, multi-disciplinary R&D team. We are looking for accomplished and highly motivated individuals who are excited to tackle the hardest, most ambiguous technical challenges at the intersection of AI, physics, and computer architecture. You will be responsible for driving the post-silicon bring-up, validation, and characterization of the core components of our novel computing platform. Responsibilities Post-Silicon Bring-up: Lead the initial power-on and bring-up of new silicon prototypes and hardware platforms in the lab. Mixed-Signal Characterization: Evaluate and benchmark the functionality, performance, and power consumption of complex mixed-signal circuits to ensure alignment with design specifications and simulation models. Hardware Debug: Utilize lab test equipment, such as oscilloscopes, logic analyzers, and power analyzers, to identify, triage, and solve anomalies across silicon, board, and software. Lab Infrastructure: Design and maintain Python-based automation frameworks to accelerate characterization throughput, test repeatability, and data reporting. Cross-Functional Collaboration: Collaborate with the System Modeling and both Analog and Digital Design teams to define validation requirements, interpret simulation-to-silicon correlation, and drive root-cause analysis. Minimum Qualifications B.S. or M.S. in Electrical Engineering, Computer Engineering, or a related field. 5+ years of industry experience in post-silicon bringup-up, hardware validation, or silicon characterization. Familiarity with operating lab test equipment (oscilloscopes, logic analyzers, power analyzers, etc). Demonstrated proficiency in characterizing and debugging mixed-signal circuits. Experience with Python programming and lab automation. Excellent written and verbal communication skills. Preferred Qualifications (Nice to Have) Experience evaluating the performance tradeoffs of current neural network architectures. Experience with correlating mixed-signal measurements on silicon to simulation models. Understanding of hardware/software co-design concepts for machine learning inference or training. Familiarity with FPGA emulation and RTL simulation to leverage pre-silicon verification for post-silicon bring-up. Familiarity with AI automation. Why Join Us? The Mission: Tackle a fundamental problem that could redefine computing for the next 50 years. The Impact: Be a foundational member of a world-class team with an outsized opportunity for ownership and impact. The Challenge: Work on deeply challenging, intellectually stimulating problems that sit at the cutting edge of multiple fields. The Perks: A comprehensive package including best-in-class health benefits, 401k matching, truly unlimited PTO, and complimentary meals in our Palo Alto office.

Requirements

Must-haves

Post-Silicon Bring-up: Lead the initial power-on and bring-up of new silicon prototypes and hardware platforms in the lab.
Mixed-Signal Characterization: Evaluate and benchmark the functionality, performance, and power consumption of complex mixed-signal circuits to ensure alignment with design specifications and simulation models.
Hardware Debug: Utilize lab test equipment, such as oscilloscopes, logic analyzers, and power analyzers, to identify, triage, and solve anomalies across silicon, board, and software.
Lab Infrastructure: Design and maintain Python-based automation frameworks to accelerate characterization throughput, test repeatability, and data reporting.
Cross-Functional Collaboration: Collaborate with the System Modeling and both Analog and Digital Design teams to define validation requirements, interpret simulation-to-silicon correlation, and drive root-cause analysis.
B.S. or M.S. in Electrical Engineering, Computer Engineering, or a related field.
5+ years of industry experience in post-silicon bringup-up, hardware validation, or silicon characterization.
Familiarity with operating lab test equipment (oscilloscopes, logic analyzers, power analyzers, etc).
Demonstrated proficiency in characterizing and debugging mixed-signal circuits.
Experience with Python programming and lab automation.
Excellent written and verbal communication skills.
Experience evaluating the performance tradeoffs of current neural network architectures.
Experience with correlating mixed-signal measurements on silicon to simulation models.
Understanding of hardware/software co-design concepts for machine learning inference or training.
Familiarity with FPGA emulation and RTL simulation to leverage pre-silicon verification for post-silicon bring-up.
Familiarity with AI automation.
Why Join Us?
The Mission: Tackle a fundamental problem that could redefine computing for the next 50 years.
The Impact: Be a foundational member of a world-class team with an outsized opportunity for ownership and impact.
The Challenge: Work on deeply challenging, intellectually stimulating problems that sit at the cutting edge of multiple fields.

Nice-to-haves

Preferred Qualifications (Nice to Have)

Application prep

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Keywords to mirror

aipythonmachine learning

Platform: greenhouse
Effort: quick

Benefits

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401k

Pto