Head of Data Acquisition

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:

Normal EDA's AI systems are only as good as the data that trains them. High-quality semiconductor datasets are exceptionally hard to come by - they require sustained outreach, creative sourcing, and close alignment with our ML team. This role exists to solve that problem at scale.

As Head of Data Acquisition, you will build and own the function responsible for sourcing, acquiring, and organizing the datasets that power Normal EDA's AI. This is a strategic, zero-to-one leadership role. You will spend most of your time identifying where valuable data lives, building trust with the organizations that hold it, and designing the internal systems that make it usable at scale.

The ideal candidate has built something from scratch before - a function, a partnership program, a data operation. You can sit down with an ML engineer to understand exactly what data they need, then walk into a conversation with a university professor and earn their trust. You don't need to be a chip design expert, but you need to be credible with people who are, and excited to learn the domain.

Responsibilities:

• Defining and owning Normal EDA's semiconductor data acquisition roadmap in close collaboration with ML engineers and product teams - translating model needs into sourcing priorities and managing a data budget to maximize impact.
• Measuring and improving the quality of acquired datasets - building the evals and data science infrastructure needed to assess what we have and identify what we're missing.
• Managing contractors and annotation teams responsible for creating and labeling data, ensuring output meets quality standards and project timelines.
• Procuring datasets through licensing, purchasing, and data-sharing agreements - identifying sources, coordinating outreach, and managing agreements end-to-end.
• Building internal tooling to support the data function: eval frameworks, annotator tools, ingestion pipelines, and versioning systems.
• Coordinating with engineers (internal and external) to define data requirements and validate acquired semiconductor data before it enters training or evaluation pipelines.
• Evaluating build vs. buy vs. partner options for each data type as the function scales.

What Makes You A Great Fit:

• 5+ years of experience as a PM, TPM, or operations leader at a high-growth tech company, with a track record of leading complex, multi-stakeholder programs end-to-end.
• Practical data and evals expertise - whether as an engineer, PM, or researcher, you understand what makes data high-quality and how to design evaluations around it.
• You've built something from scratch before - a function, a partnership program, a data operation. You know what zero-to-one feels like and you're energized by it.
• Willing and able to use AI to write code.
• Scrappiness and bias for action. You operate well with ambiguity, move fast, and figure out what you need as you go.
• B.Sc or M.Sc in Computer Science, Data Science, Engineering, or a related technical field.

Bonus Points For:

• Experience at a data-centric AI company or any company where data was a primary strategic asset.
• Familiarity with the semiconductor or chip design industry - you don't need to be an engineer, but the ability to learn the domain quickly and earn the respect of chip designers is a significant advantage.
• Experience managing data annotation programs or working with crowdsourced data platforms.