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Alljoined

Data Infrastructure Engineer

San Francisco$140k–$180kfulltimemidAdded 1 month ago

About this role

Alljoined seeks a Data Infrastructure Engineer to build the backend systems enabling brain-computer interface research. You'll design and manage the entire data pipeline—from processing massive multimodal datasets through cloud and bare-metal clusters—to support foundational model training at scale.

What you'll do

  • Build and maintain high-performance ETL pipelines processing terabytes of daily multimodal data (video, audio, text, time-series)
  • Architect, provision, and manage bare-metal compute clusters, storage servers, and networking infrastructure for ML workloads
  • Design storage topologies and manage databases (TimescaleDB, ClickHouse) across hybrid on-premise and cloud environments
  • Bridge neuro hardware systems with central data repositories to ensure low-latency, high-throughput delivery to GPUs
  • Optimize data ingestion from heterogeneous hardware peripherals while maintaining data integrity and concurrent stream handling
  • Own the complete infrastructure lifecycle from I/O optimization to production deployment and monitoring

What they're looking for

  • Systems-level architecture and production software engineering (3+ years)
  • Python, Rust, C++, or Go
  • High-performance ETL pipeline design for large-scale unstructured data
  • Bare-metal cluster provisioning and management
  • Database management (TimescaleDB, ClickHouse) and distributed storage
  • Cloud platforms (AWS/GCP/Azure) and hybrid infrastructure
  • ML frameworks (PyTorch/TensorFlow) and GPU utilization optimization
  • Networking for distributed systems (InfiniBand, RoCE, zero-copy networking)

Benefits

  • Competitive equity compensation at seed stage
  • Housing support options
  • Visa sponsorship
  • 3% 401k matching
  • Health insurance
  • $140,000 - $180,000 annual compensation
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Alljoined

Alljoined builds infrastructure and machine learning systems for non-invasive brain-computer interface research, focusing on processing and decoding EEG neural signals at scale. The company is hiring Software Engineers, Machine Learning Researchers, and Data Infrastructure Engineers to develop data pipelines, deep learning models, and backend systems that power neural decoding experiments.

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Likely interview questions

  • Walk us through a high-performance ETL pipeline you've built. How did you handle data validation, buffering, and ensuring no data loss at scale?
  • Describe your experience managing bare-metal compute clusters and storage infrastructure. What challenges did you face and how did you optimize for ML workloads?
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