Normal Computing Corporation
Research Engineer, Agentic EDA

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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.
Your Role in Our Mission
We’re hiring a Research Engineer to push the frontier of agentic LLMs and reinforcement learning for pushing the capabilities of Normal EDA, our agentic AI platform for semiconductor design automation. You’ll design and run experiments, build agents, curate datasets from complex technical artifacts, and create rigorous evaluations. You’ll write production-quality research code and work closely with engineering to ship improvements to customers.
Responsibilities
- Build multi-agent systems for code generation that interact with EDA tools (e.g., simulations, waveform analysis, formal tools, physical design tools), propose fixes, and iterate through all stages of chip design and verification flows.
- Build research prototypes that integrate with our production agentic code generation tool; collaborate to productionize wins.
- Create RL environments and evaluations for agents, explore proxy rewards and consider speed/accuracy tradeoffs of custom tools.
- Generate datasets from silicon collateral (e.g., RTL, testbenches, custom VIPs) sources such as RTL designs/VIPs/chip specifications/agent logs; generate synthetic data where appropriate; maintain data cards and licensing.
- Analyze experiments with disciplined ablations; document results and drive progress with technical rigour.
- Stay current on LLM agents, RL (offline/online, RLHF/RLAIF), constrained decoding, and program synthesis.
Reasons to use Rodeo
I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?
Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.
Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.
Start with a chat, not a search bar
Grad scheme, placement, apprenticeship? Not sure what you want yet — that's fine. Your agent talks it through with you and turns "I have no idea" into a shortlist.
Graduate Consultant — 2026 Scheme
Why you're a good match
StrongYour economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.
See breakdownIt searches the market for you
Every day your agent scans the market matching roles against what actually matters to you, not just keywords on a CV.
Why you're a good match
You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.
Experience fit
Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.
Only hits
No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.
What Makes You a Great Fit
- PhD in CS/AI/ML (or equivalent research experience) with publications ideally in multi-agent RL, agentic AI, or RL for language/code.
- Strong Python and ML framework experience (PyTorch preferred; JAX/HF a plus).
- Demonstrated ability to turn research into working systems.
- Experience designing evaluation environments and reward models for sequential/agentic tasks.
- Experience and fluency with EDA tools (formal, simulation, physical design).
- Comfortable with data acquisition/curation; good instincts about data quality and licenses.
- Clear communicator who partners well with other engineers.
Bonus Points


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Your very own career expert that helps elevate your application to the next level.
- Research on program synthesis/codegen, constrained decoding, or execution-based rewards.
- Experience with offline RL from tool traces or human corrections.
- Open-source contributions (e.g., SkyRL, verl, RLlib, Transformers, Pytorch).
- Familiarity with semiconductor/chip domains or other complex technical domains.
- Track record of shipping research to production.
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.
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