Forward Deployed Engineer

Normal Computing Corporation; New York (NY); On-site; USD 100,000 - 150,000; Full time

Job summary

Normal Computing Corporation in New York is seeking a Forward Deployed AI Engineer to work directly with enterprise customers in adapting their ML systems to fit proprietary silicon design workflows. You'll bridge the gap between customer needs and Normal's offerings, ensuring successful implementations.

The ideal candidate has experience in shipping ML systems within production environments, a strong background in hardware and semiconductor verification, and a solid foundation in software engineering. The role offers a chance to make impactful decisions and contributes to shaping future developments.

Qualifications

• Track record of shipping ML systems in customer environments.
• Interest in hardware, electrical engineering, and chip design.
• Fluency in semiconductor verification workflows.
• Strong software engineering fundamentals.
• Experience with prompt engineering and model deployment.

Responsibilities

• Adapt existing platforms to customer data and workflows.
• Bridge customer engineering and ML systems.
• Embed with customer silicon engineers.
• Make crucial development judgment calls.
• Codify successful approaches into reusable patterns.
• Provide feedback to core teams on customer needs.

Skills

Experience shipping ML systems

Knowledge of semiconductor verification

Proficient in Python

Hands-on ML stack experience

Ability to work in ambiguity

Tools

SystemVerilog

UVM testbenches

Job description

Normal Computing | Incredible Opportunities

The Normal Team builds foundational software and hardware that help move technology forward, supporting the semiconductor industry, critical AI infrastructure, and the broader systems that power our world. We work as one team across New York, San Francisco, Copenhagen, Seoul, and London.

Your Role in Our Mission

Silicon engineering is defined by exponential growth in design complexity, shrinking first‑silicon success rates, and a global shortage of specialized talent. Normal EDA addresses these constraints with a platform that builds structured, traceable engineering artifacts directly from specifications and learns continuously from the teams that use it. The Forward Deployed Engineer is the person who makes that work inside customer environments, adapting the platform to their data, their workflows, and the engineering judgment their teams carry.

We are hiring Forward Deployed AI Engineers to embed inside enterprise customers' silicon design environments and adapt Normal EDA to their data, workflows, and design challenges. You will work inside a pod with Deployment Strategy, Platform, other FDE, and GTM team members on a single enterprise engagement, and you will own the ML systems that make the platform work inside that customer's environment.

Responsibilities

• Adapt Normal EDA to each customer's proprietary data, design flows, and tooling. Validate generated artifacts against their specifications, and design evals against real customer workflows so model behavior holds up in production.
• Bridge between customer engineering artifacts and the ML systems that operate on them. You will need to understand both sides well enough to diagnose whether a problem is in the model, the data, or the workflow.
• Embed with silicon engineers at the customer. Translate their constraints back to Normal's research, product, and platform teams, and shape what the platform becomes based on what you learn in the field.
• Make judgment calls on what to build, what to skip, and when to push back on a customer request that would compromise the quality of what ships. You will regularly operate ahead of a playbook.
• Codify what works on each engagement into reusable patterns that raise the floor for every engagement after yours.
• Bring field signal back to Normal's core ML and product teams. Your read on what customers actually need will directly shape model and platform investment priorities.

What Makes You A Great Fit

• Track record of shipping ML systems inside customer or production environments where model behavior had to hold up against real‑world data. You may have been called an AI FDE, an Enterprise Tech Lead, or something else entirely.
• An interest in hardware, electrical engineering, and how chips get designed and built. If your background is in semiconductor verification, hardware engineering, or a related domain and you are building ML depth, that combination is a strong fit for this role.
• 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.
• 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, RAG, agentic patterns, model deployment.
• Calm in ambiguity. You make good decisions with incomplete information, and you know when to act and when to ask.

Bonus Points For

• Direct experience with EDA, semiconductor design flows, verification workflows (UVM, SystemVerilog, coverage‑driven verification), or other formal/structured engineering domains.
• 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 [e-mail].

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