Machine Learning Data Engineer, Parallel Domain

• Data engineering experience: Proven experience building scalable data pipelines and tooling
• ML-aware engineering: Understanding of how data is used in model training and evaluation
• 3D Foundations: Practical experience with 3D concepts, geometry, and the linear algebra principles underpinning computer vision (e.g., projections, transformations)
• Technical skills: Strong Python proficiency and comfort with large datasets
• Collaborative mindset: Experience working closely with ML engineers on data needs

Desirable

• We are hiring a Machine Learning Data Engineer responsible for building and scaling the data pipelines that support Replica and ML model development. You will ensure that data flows efficiently from raw customer inputs through validated, structured formats suitable for training, evaluation, and production systems
• Own data ingestion: Build reliable pipelines to normalize and validate customer and synthetic data
• Define data standards: Create schemas, validation checks, and quality metrics for Replica datasets
• Build curation tooling: Implement tools for dataset filtering, versioning, and annotation support
• Enable ML workflows: Generate high-quality data feeds for training and evaluation across ML models