Overview:
In this role within the Frontier AI Organization, you will design and scale data preparation pipelines that feed next-generation model development. You will collaborate with scientists, ML engineers, and product teams to deliver production-ready datasets and ensure data quality at scale. You’ll leverage cloud-native technologies to handle petabyte-scale datasets and drive impact on model training timelines. This is a hands-on position that blends systems design, data engineering, and cross-functional collaboration to power AI innovations. Compensation / Benefits health insurance (medical, dental, vision) 401(k) matching RSUs sign-on payments paid time off parental leave
Responsibilities:
Architect and build scalable data processing systems to ingest, transform, and enrich large-scale datasets across multiple languages Develop automated data quality validation, tracking, and drift-detection mechanisms Optimize end-to-end data pipelines from ingestion to delivery to accelerate model training Collaborate with applied scientists, ML engineers, and product teams to define data requirements and produce production-ready datasets Leverage cloud-native technologies to process petabyte-scale corpora efficiently and cost-effectively
Key requirements:
3+ years non-internship software development experience 2+ years design or architecture experience on large-scale systems 1+ years SDE or related occupation experience 1+ years designing and developing large-scale, distributed software applications 1+ years of Object Oriented Design experience Experience programming in C#, C++, Java, or Perl Bachelor's degree or foreign equivalent in Computer Science, Engineering, Mathematics, or a related field Preferred: 3+ years full software development lifecycle including coding standards, code reviews, SCM, build, testing, and operations cross-functional collaboration strong problem-solving data quality discipline C# C++ Java