Hardware Engineer, Normal Computing
Physical Design
Generative AI for enterprise
Open for applications
Generative AI for enterprise
21-100 employees
Open for applications
21-100 employees
Company mission
To bridge artificial intelligence to the most sensitive industrial and advanced manufacturing applications around the globe.
Role
Who you are
- Experience working on AI accelerators, novel or non-traditional computing architectures
- Background that blends research and production (e.g., research tape-outs, internal tools, early-node or first-of-kind silicon)
- Evidence of first-principles thinking in physical design, rather than reliance on established flows
- Contributions to flow development, methodology papers, internal tools, or open-source EDA/software projects
- Experience in startup environments or small, high-ownership teams
- Comfort collaborating across disciplines (architecture, circuits, modeling, systems, or packaging)
- Demonstrated mentorship or technical leadership beyond individual contribution
- 7+ years of experience in silicon physical design, or equivalent depth demonstrated through complex tape-outs, research prototypes, or unconventional design work
- Proven ownership of physical design flows and methodologies, beyond execution within an existing flow
- Strong hands-on experience with place & route, timing closure, and physical signoff, even when constraints or architectures are non-standard
- Proficiency in scripting and automation (Tcl, Python, or similar) to build and evolve custom PD flows
- Ability to operate independently in an ambiguous, fast-moving R&D environment and drive work from concept to silicon
What the job involves
- As a Physical Design Engineer at Normal, you will work closely with the silicon and hardware R&D team to develop and implement novel thermodynamic computing architectures
- You will have significant ownership of chip floorplanning, top-level integration, and signoff, with the goal of delivering reliable silicon and achieving first-silicon-success
- Lead physical design for a novel silicon-based computing architecture through tape-out and iteration
- Implement full chip and layout blocks. Procure and integrate IP
- Own and evolve the physical design flow end to end, including tool selection, methodology definition, automation, and continuous improvement
- Translate unconventional architectural and circuit concepts into robust, manufacturable layouts, making tradeoffs across PPA and feasibility
- Drive floorplanning, power delivery, clocking, and implementation
- Partner with architecture, circuit, modeling, and systems teams to co-design hardware and physical implementation
- Develop custom scripts, checks, and analysis tools (Tcl/Python or similar) to enable rapid experimentation and design space exploration
- Act as a technical leader in a fast-moving startup environment, mentoring others and helping shape long-term silicon and methodology strategy
Salary benchmarks
Our take
As the rate of AI adoption accelerates, Normal Computing sets out to make it more usable and scalable for enterprises, where risk is a central barrier to its implementation. The hope is that this will allow enterprises to make use of technologies such as Generative AI which has so far only been considered appropriate for early consumer applications.
The company's Probabilistic AI gives control over reliability, adaptivity, and auditability to AI models powered by its customers' private data. It boasts the ability to support such applications as automating complex underwriting processes, generating and validating specialized code, and mitigating risks in situations where the conditions are dynamic and fluctuating.
By targeting a major roadblock to enterprise AI adoption, Normal Computing has the chance to make a major (and profitable) contribution to accelerating complex AI use cases. The company has raised considerable funding to support its endeavours, which it will use to double down on the R&D of its application development platform and Probabilistic AI technology.
Freddie
Company Specialist at Welcome to the Jungle
Company
Funding (last 2 of 3 rounds)
Nov 2024
$66.8m
GRANT
Jun 2023
$8.5m
SEED
Total funding: $83.8m
Company HQ
Civic Center, New York, NY
Leadership
Faris Sbahi
(Co-Founder & CEO)Has worked as a Research Scientist at X, the moonshot factory, a Software Engineer at Google, and as a Forward Deployed Engineer at Palantir Technologies.
Matthias Tan
(Co-founder)Venture Partner at NextGen Venture Partners. Former Principal of Strategy and Partnerships at X, the moonshot factory, and Director of Product and Partnerships at Pony.ai.
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