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Full-Time

Mixed Signal Design Engineer

Confirmed live in the last 24 hours

Normal Computing

Normal Computing

1-10 employees

Develops generative AI for enterprises

AI & Machine Learning
Enterprise Software

Mid, Senior

London, UK

Category
Hardware Engineering
Electronic Hardware Engineering
Required Skills
Verilog
Python
Perl
Requirements
  • Experience working on analog-to-digital and/or digital-to-analog converters that push the envelope in terms of performance, power consumption, accuracy, or area.
  • Proficiency with VerilogA for modeling analog and mixed-signal circuits and devices, and experience leveraging those models to deliver system-level performance estimates.
  • Experience in Verilog and/or SystemVerilog.
  • Experience in scripting languages, including Python, Perl, and/or TCL.
  • Proficiency with Cadence Virtuoso for design and layout of analog blocks.
  • Understanding of design and layout techniques to minimize mismatch and parasitics while maximizing performance.
  • Strong understanding of design for manufacturability, transistor mismatch, and yield.
  • Excellent communication skills and the ability to work well on a small, interdisciplinary team.
Responsibilities
  • You will play a key role in the entire development process of our silicon, from idea to architecture to implementation to tape-out.
  • Contribute new ideas for potential thermodynamic computing technologies and architectures.
  • Implement analog and mixed-signal components in Cadence Virtuoso, potentially including analog-to-digital converters, amplifiers, memory cells, and oscillators.
  • Perform layout, parasitic extraction, and optimization of Normal’s thermodynamic computing circuits.
  • Participate in the tape-out, bring-up, and testing of Normal’s silicon.

Normal Computing develops generative AI specifically for critical enterprise applications, focusing on large-scale enterprises like Fortune 500 companies in sectors such as semiconductor manufacturing, supply chain management, banking, and government. Their technology, based on Probabilistic AI, utilizes statistical analysis to predict outcomes, allowing businesses to have greater control over the reliability, adaptivity, and auditability of their AI models. This approach addresses the significant risks that have hindered AI adoption in these industries. Unlike many competitors, Normal Computing tailors its AI solutions to meet the specific needs of its clients, operating on a subscription or contract basis. The goal of Normal Computing is to mitigate risks associated with AI implementation, making it a more viable option for enterprises.

Company Stage

Seed

Total Funding

$8.5M

Headquarters

New York City, New York

Founded

2022

Growth & Insights
Headcount

6 month growth

36%

1 year growth

28%

2 year growth

412%
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Simplify's Take

What believers are saying

  • Normal Computing's innovative technology could lead to widespread adoption among Fortune 500 companies, significantly boosting revenue and market presence.
  • Their focus on risk management in AI applications makes them highly attractive to industries that have been hesitant to adopt AI due to potential risks.
  • The strong background of the founding team enhances credibility and attracts top-tier talent, fostering a culture of innovation and excellence.

What critics are saying

  • The high level of customization required for each client could limit scalability and strain resources.
  • Operating in a rapidly evolving AI market means Normal Computing must continuously innovate to stay ahead of competitors.

What makes Normal Computing unique

  • Normal Computing leverages Probabilistic AI to offer unprecedented control over AI model reliability, adaptivity, and auditability, setting it apart from traditional AI solutions.
  • The company's founders come from elite backgrounds at Google Brain, Palantir, and X, providing a strong pedigree and deep expertise in AI.
  • Normal Computing focuses on high-risk industries like semiconductor manufacturing and banking, where their risk-mitigating AI solutions are particularly valuable.