---
title: 'Forward Deployed Engineer at Normal Computing Corporation'
canonical: 'https://feeny.ai/job/forward-deployed-engineer-normal-computing-corporation-new-york-nncgjxbr6adq'
type: 'job'
last_seen: '2026-09-10'
---

# Forward Deployed Engineer at Normal Computing Corporation

- **Company:** Normal Computing Corporation
- **Location:** New York, NY
- **Employment:** full-time
- **Work type:** hybrid
- **Posted:** 2026-06-08
- **Last confirmed live:** 2026-09-10
- **Apply:** https://jobs.ashbyhq.com/normalcomputing/a1829ea4-36fc-42a9-af1d-5382f121ccf7

## Job description

Normal Computing | Build with Us Normal is an applied AI company solving the hardest problems in AI and silicon. We build foundational hardware and software for the semiconductor industry, critical AI infrastructure, and the broader systems that power our world, in partnership with the world's most advanced institutions. We work as one team across New York City, Silicon Valley (Mountain View), London, Copenhagen, and Seoul.

## The Role

The cost of taping out silicon is enormous, and the complexity of verification makes multiple tapeouts hard to avoid. Normal EDA accelerates this work as an AI platform for collaborative silicon engineering: a single source of truth across the chip lifecycle, learning continuously from the teams that use it. As a Forward Deployed Engineer, you own our EDA system inside a customer's environment. Embedded directly with our partners, you adapt our platform to their data, workflows, and design challenges, working alongside our account executive and a deployment strategist to make the deployment a success. You thrive as a problem-solver and take pride in winning over customers along with the rest of your team. You will be debugging distributed systems, building new product features, post-training models, and working in various silicon-native languages such as SystemVerilog. Note that many different kinds of candidates could be well-qualified for this role, even with non-overlapping expertise (e.g. ML background vs. silicon background).

## What You Will Own

- Production Problem-Solving: Diagnose issues in our system, the model, the data, or the workflow. Work deep in both Normal's systems and the customer's environment to resolve them, and close the loop with their engineers.
- Evaluation Against Reality: Design and run evals against real customer workflows, validating generated artifacts against their specifications so model behavior holds up in production.
- Platform Integration: Integrate the platform with each customer's data, design flows, and tooling, working with their production codebases and against their existing infrastructure.
- Customer Signal: Embedded with silicon design teams, translate their constraints into model and platform requirements, and carry that signal back to Normal's research, product, and platform teams to shape what gets built next.
- Continual Learning: Post-train Normal's models on-prem on proprietary customer data and trajectories to customize to their workflow, tooling, and style preferences. Build the continual-learning loops that turn their engineers' feedback into system knowledge, so model quality compounds across the engagement.
- Judgment Ahead of Playbook: Make the calls on what to build, what to skip, and when to push back on a request that would compromise what ships. Codify what works into patterns that raise the floor for every engagement after yours.

What Makes You a Great Fit

- Great at problem-solving and tracking down issues wherever they are in the stack
- Strong software engineering fundamentals: proficient in Python, comfortable in production codebases, distributed-systems literate
- Hands-on experience with the modern ML stack: prompt engineering, fine-tuning, evals, agentic patterns, model deployment
- Willingness and ability to go deep on semiconductor verification workflows. You will spend significant time inside UVM testbenches, SystemVerilog codebases, and design specifications. Prior experience is a strong advantage, but what matters is whether you can build fluency fast and earn credibility with verification engineers
- An ability to ship ML systems inside customer or production environments where model behavior had to hold up against real-world data
- Calm in ambiguity: you make good decisions with incomplete information, and you know when to act and when to ask
- Comfortable with travel when needed; anywhere between a few days for customer meetings and a few months for longer-term customer projects

Bonus Points

- Direct experience with EDA, semiconductor design flows, verification workflows (UVM, SystemVerilog, coverage-driven verification), or other areas of silicon engineering
- Built or led an FDE or customer-deployment function from the ground up at an earlier-stage company
- Open-source contributions or publications in AI or ML venues

## 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 accommodations@normalcomputing.com. 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.

## About Normal Computing Corporation

## Company Overview
- **One-liner**: Normal Computing builds AI-accelerated EDA software and physics-based ASICs to enable ultra-efficient hardware for the AI era.
- **Entity Type**: Private (Series B; total funding $92.5M)
- **Headquarters**: New York, New York, USA
- **Founded**: 2022
- **Founders**: Faris Sbahi (CEO), Matthias Tan (Co-Founder), and team of former Google Brain/Google X engineers and scientists

## Core Business
- Primary industry: Semiconductor design (EDA) and custom silicon (ASICs), powered by AI and probabilistic computing.
- Target customers: Large semiconductor design and manufacturing institutions (B2B, enterprise).
- Mission: "Rewriting AI foundations to advance the frontier of reasoning and reliability in the physical world" and enabling a virtuous cycle of self-improving AI hardware.

## Products & Services
- **[Normal EDA](https://normalcomputing.com/)**: An AI-driven electronic design automation platform that understands design intent from specification documents, generates hierarchical test plans with traceability, creates SystemVerilog stimulus, runs simulations, and tracks coverage. It continuously learns from team feedback to accelerate verification for complex chip designs.
- **[Normal ASICs](https://normalcomputing.com/)**: Physics-based custom ASICs that relax traditional computing assumptions (stochastic, stateful, asynchronous) to unlock orders-of-magnitude more efficient compute. Designed to converge hardware with the physical dynamics of AI models.

## Market Standing
- **Valuation/Market Cap**: Not publicly disclosed.
- **Key Metric**: **Total Funding** – $92.5M across multiple rounds (Seed, Venture, Grant, Series B). Notable recent round: $50M led by **Samsung Catalyst** in March 2026 [normalcomputing.com](https://normalcomputing.com/).
- **Notable Investors**: Samsung Catalyst Fund, Intel Ignite, First Spark Ventures, Celesta Capital, ARIA. Also partners with Fraunhofer IESE (DRAMBench benchmark).
- **Growth Signals**: Headcount grew **196.3% YoY** to 54 employees; operates across 6 countries (US, UK, Denmark, Switzerland, India, Canada); actively building open-source tools (e.g., a Verilog simulator built with AI: 580K lines in 43 days).

## Competitive Advantages
- **Physics-First Approach**: Unlike traditional digital logic, Normal’s ASICs embrace stochastic, stateful, and asynchronous computing – aligning hardware with the physics of AI models for dramatic efficiency gains.
- **Full-Stack Co-Design**: The combination of AI-native EDA tools and custom silicon creates a closed loop where software and hardware are co-optimized, shortening time-to-market and enabling workload-specific ASICs.
- **Deep AI Heritage**: Founders and team hail from Google Brain and Google X, bringing deep expertise in probabilistic ML, quantum AI, and physical-world reasoning.

## Strategic Focus
- **Scaling EDA Adoption**: Expanding Normal EDA’s use among top semiconductor companies to "make chip design look more like software".
- **AI Hardware Energy Crisis**: Tackling soaring power demands of AI by delivering ultra-efficient ASICs that can be produced for every workload.
- **Open-Source & Research**: Building community trust through open benchmarks (DRAMBench) and tools (CIRCT-based verification), while advancing formal methods and AI-driven simulation.

## Why Work Here
- **Hybrid Workspace**: Flexible in-office collaboration at offices in **New York (Flatiron HQ)**, **San Francisco**, **London**, and **Copenhagen**. In-person collaboration is valued but with flexibility; free lunch, snacks, and beverages in office.
- **Lean, High-Impact Team**: Small team (54 employees) where every member drives significant impact, works directly with customers, and owns meaningful parts of the product.
- **Interdisciplinary Challenges**: Work spans AI, probabilistic software, hardware, physics, and full-stack engineering – ideal for curious, passionate problem-solvers.
- **Strong Growth Trajectory**: Rapid headcount growth (+196% YoY), recent $50M Series B, and partnerships with industry giants signal a well-funded, high-potential startup.

## Sources
1. [normalcomputing.com](https://normalcomputing.com/)
2. [normalcomputing.com/about](https://normalcomputing.com/about)
3. [linkedin.com/company/normal-computing-corporation](https://www.linkedin.com/company/normal-computing-corporation)
4. [builtin.com/company/normal-computing](https://builtin.com/company/normal-computing)
5. [jobs.ashbyhq.com/normalcomputing](https://jobs.ashbyhq.com/normalcomputing)

## Other roles at Normal Computing Corporation

- [Hardware Engineer, System Design](https://feeny.ai/job/hardware-engineer-system-design-normal-computing-corporation-silicon-valley-ewmb4smy3n8k) — Silicon Valley
- [Research Engineer, Agentic EDA](https://feeny.ai/job/research-engineer-agentic-eda-normal-computing-corporation-new-york-n9n5s5w4myky) — New York, NY
- [Software Engineer, Terminal Interface](https://feeny.ai/job/software-engineer-terminal-interface-normal-computing-corporation-new-york-4wm9d2tfm0ja) — New York, NY
- [Talent Operations Specialist](https://feeny.ai/job/talent-operations-specialist-normal-computing-corporation-silicon-valley-rj0rjeg87g4x) — Silicon Valley
- [Thermodynamic Hardware Resident](https://feeny.ai/job/thermodynamic-hardware-resident-normal-computing-corporation-new-york-jg4avbjrxt43) — New York, NY
- [AI Research Resident](https://feeny.ai/job/ai-research-resident-normal-computing-corporation-new-york-44frw5ybhavm) — New York, NY
- [Hardware Engineer, Lead Architect](https://feeny.ai/job/hardware-engineer-lead-architect-normal-computing-corporation-silicon-valley-6fvq60qmptdw) — Silicon Valley
- [Hardware Engineer, FPGA](https://feeny.ai/job/hardware-engineer-fpga-normal-computing-corporation-new-york-4v6epje87dne) — New York, NY
- [Software Engineer, Agent Systems](https://feeny.ai/job/software-engineer-agent-systems-normal-computing-corporation-new-york-9mc74m2d7yp9) — New York, NY
- [Research Engineer, Domain Scaling](https://feeny.ai/job/research-engineer-domain-scaling-normal-computing-corporation-new-york-f308m76kzev4) — New York, NY