Staff Silicon Characterization Engineer at Untether AI

Toronto, Ontario, Canada

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Not SpecifiedCompensation

Senior (5 to 8 years)Experience Level

Full TimeJob Type

UnknownVisa

Semiconductors, Artificial IntelligenceIndustries

Requirements

Candidates should possess 7+ years of experience in binning large chips such as CPUs, GPUs, SOCs, and NICs, along with a deep understanding of silicon variation across process, frequency, and temperature. Experience with yield recovery, repair, or floor sweeping is preferred, and clear vision for organizing and presenting data is essential.

Responsibilities

The Staff Silicon Characterization Engineer will own all technical aspects of chip binning, from designing experiments to analyzing data and making recommendations on how to bin chips to optimize performance, power, and yield. They will collaborate with the Product Team to set product definitions, establish requirements for the Validation Team, and correlate results with ATE, while also participating in chip design as needed. Furthermore, they will contribute to ensuring the delivery of the best product through cross-functional collaboration with technical and non-technical teams.

Skills

chip binning

silicon characterization

experiment design

data analysis

yield recovery

silicon variation

ATE correlation

floor sweeping

Untether AI

Enhances AI inference with at-memory computing

About Untether AI

Untether AI enhances the speed and efficiency of AI inference workloads using at-memory computing. This method places the compute element next to memory cells, which boosts compute density and accelerates AI inference for various neural networks, such as those used in vision, natural language processing, and recommendation systems. The company targets businesses that rely on AI technologies and need high-performance computing for inference tasks. Their products, including the runAI200® devices and tsunAImi® accelerator cards, are designed to deliver exceptional performance, with the tsunAImi® card offering over 2 PetaOps. This allows businesses to optimize their AI workloads while maintaining a compact PCI-Express form factor. Untether AI's goal is to provide efficient and cost-effective solutions for companies looking to enhance their AI applications.

Toronto, CanadaHeadquarters

2018Year Founded

$144.6MTotal Funding

SERIES_BCompany Stage

Hardware, AI & Machine LearningIndustries

51-200Employees

Benefits

Paid Vacation

Health Insurance

Unlimited Paid Time Off

Stock Options

Risks

Emerging competition in energy-efficient AI hardware could threaten market position.

Rapid AI model evolution may require frequent hardware updates and innovations.

Supply chain vulnerabilities in semiconductor components could impact production timelines.

Differentiation

Untether AI's at-memory computing maximizes AI inference efficiency and speed.

The tsunAImi® accelerator card delivers over 2 PetaOps per card, optimizing AI workloads.

Untether AI's imAIgine SDK allows rapid deployment of neural networks with flexible kernels.

Upsides

Collaboration with Arm enhances solutions for ADAS and AV applications in the automotive sector.

$20 million funding supports ongoing development of machine learning inferencing hardware.

Partnership with J-Squared opens new opportunities in defense and commercial sectors.

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