Data Acquisition Lead (AI)

Location: On-site in San Francisco, California; London; or New York, New York.

Company

hirify.global is a research lab building open models designed to make intelligence accessible, customizable, and broadly usable.

What you will do

• Build, mentor, and grow a high-performing team of data ingestion engineers while supporting their professional development.
• Lead the full ingestion stack across web crawling and acquisition, extraction and normalization pipelines, data lakes, corpus versioning, delivery, and acquisition campaigns.
• Guide technical and architectural decisions around crawler design, politeness and scheduling, distributed processing, orchestration, storage formats, object stores, lakehouse architectures, deduplication, and dataset delivery.
• Stay hands-on by making targeted individual contributions and maintaining deep technical understanding of the stack.
• Prioritize execution across concurrent data campaigns and partner with pre-training, data quality, data partnerships, digitization operations, external vendors, and legal teams.
• Run experiments to evaluate crawling strategies, extraction methods, and ingestion tradeoffs, connecting ingestion decisions to downstream model impact.

Requirements

• Experience building, mentoring, and growing data or infrastructure engineering teams while remaining technically hands-on.
• Deep experience building web-scale data acquisition or ingestion systems, with ownership of production-grade pipelines at multi-terabyte to petabyte scale.
• Strong coding ability and the credibility to earn the technical trust of a strong engineering team.
• Deep expertise in at least one of web crawling and acquisition, large-scale extraction and ingestion pipelines, or data lakes and corpus storage and delivery, with working knowledge of the other areas.
• Fluency with distributed compute tools such as Ray, Beam, and Spark; orchestration tools such as Airflow and Prefect; formats including Parquet, JSONL, and WARC; and object-store and data-lake architectures.
• Familiarity with LLM training and evaluation, including an intuition for useful training data, experiment design, and proxy quality signals.
• Ability to guide strategy and drive execution across concurrent data campaigns and collaborate with research teams, external data vendors, partnerships, and legal.
• Ability to grow into leading a larger team quickly if prior management experience was not at that scale.

Culture & Benefits

• Talent-dense environment focused on building open foundational models from the ground up.
• Salary and equity structured to recognize and retain talent globally, with stock options for employees.
• Comprehensive medical, dental, vision, and life insurance, plus an annual wellness allowance.
• Daily lunch and dinner provided in the office.
• Twenty-two weeks of paid parental leave for birthing and non-birthing parents, including adoptive and surrogate journeys.
• Unlimited paid time off in the U.S. and 30 vacation days in the U.K., visa sponsorship, regular off-sites, happy hours, and team celebrations.

Hiring process

• Employment may be conditioned on the ability to provide access to technology or source code under U.S. export control requirements.