Head of Data Acquisition at Jobgether – United States

This position is posted by Jobgether on behalf of a partner company. We are currently looking for a Head of Data Acquisition in the United States.

This is a high-impact, foundational leadership role responsible for building the data acquisition engine that powers advanced AI systems in a highly technical and rapidly evolving domain. You will define how critical semiconductor datasets are identified, accessed, and operationalized, working at the intersection of machine learning, engineering, and industry partnerships. The role requires deep engagement with complex, fragmented data ecosystems where information is often locked within specialized workflows or distributed across inconsistent sources. You will translate model and product needs into actionable data strategies, ensuring high-quality inputs for training and evaluation. Operating in a zero-to-one environment, you will shape both the technical and relational infrastructure needed to secure and scale unique datasets. This is a highly cross-functional role involving close collaboration with ML engineers, domain experts, and external partners across the semiconductor landscape.

• Own and define the end-to-end data acquisition strategy, translating machine learning and product requirements into clear sourcing priorities for semiconductor datasets.
• Identify, evaluate, and unlock high-value data sources across semiconductor design and verification workflows, including both proprietary and open-source ecosystems.
• Build and manage strategic external partnerships, including data licensing agreements, vendor relationships, and long-term collaboration frameworks.
• Evaluate and curate datasets, establishing processes to assess quality, filter noise, and ensure usability for model training and evaluation.
• Collaborate closely with ML and engineering teams to define data requirements and ensure seamless integration into downstream systems.
• Design lightweight operational systems for data ingestion, validation, enrichment, and iteration in partnership with technical teams.
• Oversee external vendors, contractors, or annotation efforts to structure and improve data quality where needed.

This role requires deep familiarity with semiconductor or EDA ecosystems and a strong understanding of how technical datasets are generated and applied in real-world engineering or ML contexts. Candidates should have a proven track record of sourcing, acquiring, or working with complex datasets in technical environments. Experience building external partnerships and navigating ambiguous or non-standard data access scenarios is essential. Strong cross-functional communication skills are required, with the ability to operate effectively between engineering teams and external industry stakeholders. The ideal candidate thrives in zero-to-one environments, demonstrating high autonomy, ownership, and comfort with ambiguity. Exposure to machine learning systems, data-centric product development, or data operations is highly advantageous.

• Competitive compensation package aligned with senior leadership responsibilities
• Opportunity to build a foundational function from the ground up in a cutting-edge AI environment
• High-impact role with direct influence on model performance and product capabilities
• Close collaboration with world-class ML, engineering, and domain experts
• Dynamic, fast-moving environment with strong ownership and autonomy
• Opportunity to work across global teams in a highly technical and innovative organization.