Data Engineer building modern Data Lake architecture on AWS and implementing scalable ETL/ELT pipelines. Collaborating across teams for analytics and reporting on gaming platforms.
About the role
- Data Engineer building data infrastructure at Aldea, a multi-modal AI company. Designing and scaling data pipelines for language and speech domains at large token scales.
Responsibilities
- Build and scale data pipelines for pretraining, midtraining, and post-training at trillion+ token scale across language and speech domains
- Process and curate large-scale datasets including cleaning, deduplication, quality filtering, and optimization for distributed training
- Generate synthetic data for model training and evaluation across diverse tasks and domains
- Design efficient data loading systems achieving high throughput across multi-node training clusters
- Build data versioning and reproducibility systems to track dataset compositions and enable reproducible experiments
- Collaborate with ML engineers and researchers to optimize pipelines and improve data quality
Requirements
- Bachelor's degree in Computer Science, Engineering, or related field, or equivalent practical experience
- 3+ years of experience building large-scale data pipelines for machine learning or data-intensive applications
- Strong programming skills in Python and experience with data processing frameworks (Spark, Dask, Ray, or similar)
- Experience with data quality techniques including deduplication, filtering, and validation at scale
- Proven ability to optimize data pipelines for performance and throughput in distributed systems
- Experience working with large datasets (100GB-10TB+) and understanding of storage systems and data formats
Benefits
- Competitive base salary
- Performance-based bonus aligned with research and model milestones
- Equity participation
- Comprehensive health, dental, and vision coverage
- Flexible paid time off
Job title
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