Normal Computing builds silicon that turns thermal noise from an obstacle into a computational resource. Conventional chips spend most of their energy forcing determinism onto physics; ours compute with it. Stochastic in-memory asynchronous: the result is 10-100 more AI inference per dollar per watt.
We co-design the full stack: AI-native EDA systems in production with the worlds largest semiconductor companies and the advanced ASICs they make possible. Backed by $85M from the worlds leading deep-tech investors and built by scientists engineers and operators from the labs that built modern computing.
Normal works as one team across New York Silicon Valley London Copenhagen and Seoul. We hire people who want the hardest version of their craft across every discipline at every seniority.
The Role
As our AI Engineering Lead you will lead a team of engineers building systems for AI-native EDA and advanced hardware workflows. This work sits at the intersection of applied AI ML systems agents model evaluation software engineering and semiconductor domain complexity.
You will be responsible for setting technical direction managing execution developing engineers and staying close to the implementation details that determine whether these systems work in practice. The team is building AI systems where correctness traceability and reliability matter especially when agents are operating against formal or highly structured engineering problems.
This is a hands-on leadership role for someone who has grown from strong individual contribution into technical leadership or management. You should be comfortable moving between architecture model behavior evaluation implementation tradeoffs hiring and team development. The strongest candidates will have built meaningful AI systems in technical domains where models need to operate against real constraints.
What Youll Own
Team Leadership: Lead and manage a team of AI engineers; hire mentor and develop strong engineers as the team scales.
Technical Direction: Set direction for applied AI and ML engineering work across Normals product and platform areas.
Hands-On Depth: Stay hands-on with architecture implementation decisions code review debugging evaluation and system design; contribute directly to critical technical work when needed.
Structured AI Systems: Build AI systems that operate against structured engineering workflows formal specifications and objective correctness signals.
Cross-Functional Translation: Partner with product engineering research and leadership to translate ambiguous goals into clear technical plans.
Execution Model: Help define the operating rhythm engineering standards and execution model for the AI team; identify technical risks early and balance model quality reliability product impact and velocity.
What Makes You a Great Fit
Direct experience across AI engineering ML engineering applied AI production ML systems or AI infrastructure
Experience as a technical lead staff-level IC engineering manager or hybrid lead/manager for AI/ML engineering teams
Track record of building and shipping meaningful AI systems in production or high-impact technical environments
Strong hands-on technical ability with comfort reviewing designs debugging systems and contributing directly when needed
Experience working with LLMs RL agents model evaluation inference systems optimization or ML infrastructure
Ability to create clarity in ambiguous technical areas and help teams move quickly without losing rigor
Experience managing or mentoring engineers while maintaining close technical involvement
Strong ownership mindset and ability to operate in a small high-caliber team
Bonus Points
Experience applying agentic systems and AI to EDA semiconductor workflows circuits hardware design verification or other advanced engineering domains
Experience leading AI work in a startup research-heavy or zero-to-one product environment
Experience hiring and scaling small senior engineering teams
Equal Employment Opportunity Statement
Normal Computing is an Equal Opportunity Employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. All qualified applicants will receive consideration for employment without regard to race color religion sex sexual orientation gender identity national origin disability veteran status or any other legally protected status.
Accessibility Accommodations
Normal Computing is committed to providing reasonable accommodations to individuals with disabilities. If you need assistance or an accommodation due to a disability please let us know at
Privacy Notice
By submitting your application you agree that Normal Computing may collect use and store your personal information for employment-related purposes in accordance with our Privacy Policy.
Required Experience:
IC
About Normal ComputingNormal Computing builds silicon that turns thermal noise from an obstacle into a computational resource. Conventional chips spend most of their energy forcing determinism onto physics; ours compute with it. Stochastic in-memory asynchronous: the result is 10-100 more AI inferen...
About Normal Computing
Normal Computing builds silicon that turns thermal noise from an obstacle into a computational resource. Conventional chips spend most of their energy forcing determinism onto physics; ours compute with it. Stochastic in-memory asynchronous: the result is 10-100 more AI inference per dollar per watt.
We co-design the full stack: AI-native EDA systems in production with the worlds largest semiconductor companies and the advanced ASICs they make possible. Backed by $85M from the worlds leading deep-tech investors and built by scientists engineers and operators from the labs that built modern computing.
Normal works as one team across New York Silicon Valley London Copenhagen and Seoul. We hire people who want the hardest version of their craft across every discipline at every seniority.
The Role
As our AI Engineering Lead you will lead a team of engineers building systems for AI-native EDA and advanced hardware workflows. This work sits at the intersection of applied AI ML systems agents model evaluation software engineering and semiconductor domain complexity.
You will be responsible for setting technical direction managing execution developing engineers and staying close to the implementation details that determine whether these systems work in practice. The team is building AI systems where correctness traceability and reliability matter especially when agents are operating against formal or highly structured engineering problems.
This is a hands-on leadership role for someone who has grown from strong individual contribution into technical leadership or management. You should be comfortable moving between architecture model behavior evaluation implementation tradeoffs hiring and team development. The strongest candidates will have built meaningful AI systems in technical domains where models need to operate against real constraints.
What Youll Own
Team Leadership: Lead and manage a team of AI engineers; hire mentor and develop strong engineers as the team scales.
Technical Direction: Set direction for applied AI and ML engineering work across Normals product and platform areas.
Hands-On Depth: Stay hands-on with architecture implementation decisions code review debugging evaluation and system design; contribute directly to critical technical work when needed.
Structured AI Systems: Build AI systems that operate against structured engineering workflows formal specifications and objective correctness signals.
Cross-Functional Translation: Partner with product engineering research and leadership to translate ambiguous goals into clear technical plans.
Execution Model: Help define the operating rhythm engineering standards and execution model for the AI team; identify technical risks early and balance model quality reliability product impact and velocity.
What Makes You a Great Fit
Direct experience across AI engineering ML engineering applied AI production ML systems or AI infrastructure
Experience as a technical lead staff-level IC engineering manager or hybrid lead/manager for AI/ML engineering teams
Track record of building and shipping meaningful AI systems in production or high-impact technical environments
Strong hands-on technical ability with comfort reviewing designs debugging systems and contributing directly when needed
Experience working with LLMs RL agents model evaluation inference systems optimization or ML infrastructure
Ability to create clarity in ambiguous technical areas and help teams move quickly without losing rigor
Experience managing or mentoring engineers while maintaining close technical involvement
Strong ownership mindset and ability to operate in a small high-caliber team
Bonus Points
Experience applying agentic systems and AI to EDA semiconductor workflows circuits hardware design verification or other advanced engineering domains
Experience leading AI work in a startup research-heavy or zero-to-one product environment
Experience hiring and scaling small senior engineering teams
Equal Employment Opportunity Statement
Normal Computing is an Equal Opportunity Employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. All qualified applicants will receive consideration for employment without regard to race color religion sex sexual orientation gender identity national origin disability veteran status or any other legally protected status.
Accessibility Accommodations
Normal Computing is committed to providing reasonable accommodations to individuals with disabilities. If you need assistance or an accommodation due to a disability please let us know at
Privacy Notice
By submitting your application you agree that Normal Computing may collect use and store your personal information for employment-related purposes in accordance with our Privacy Policy.