Role OverviewWe are seeking an ML Data Engineer to build and operate the large-scale data systems that power modern AI training and evaluation pipelines.
What You Will Do
The role combines deep data engineering expertise with a strong understanding of AI workloads, focusing on ingestion, transformation, quality assurance, lineage, and high-throughput delivery of data to training jobs across diverse modalities.
Why It Might Be a Fit
The ideal candidate has experience operating petabyte-scale data systems, strong software engineering fundamentals, and clear understanding of how data infrastructure choices propagate into model quality and training efficiency.
Requirements
- Bachelor’s or Master’s degree in Computer Science or a related field.
- Six or more years of data engineering experience, with significant work supporting ML or AI workloads.
- Strong proficiency in Python and at least one JVM or systems language.
- Deep experience with modern data processing frameworks such as Spark, Ray, or Beam.
- Hands-on experience operating petabyte-scale storage and pipeline systems.
- Strong understanding of distributed systems, data modeling, and storage formats.
- Experience with dataset versioning, lineage, and reproducibility for ML workflows.
- Familiarity with high-throughput data loading for accelerator-based training.
- Strong software engineering practices including testing, CI/CD, and code review.
- Excellent communication and cross-functional collaboration skills.
Benefits
- Dental insurance
- Vision insurance
- Health insurance
- Paid time off
- Retirement plan
- Stock options
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