Founding Engineer - Software (Data/ML Infra)
Tasks
- Build and maintain multimodal data pipelines
- Build and optimize machine learning training workflows
- Build distributed training infrastructure
- Build infrastructure for teleoperation model training and deployment
- Collaborate on technical roadmap and infrastructure strategy
- Design cloud infrastructure for scalable model training
- Design cloud storage for multimodal robotics datasets
- Design compute orchestration for training workloads
- Design robotics dataset ingestion and querying systems
- Develop tooling for exploration of robotics field logs
- Establish engineering best practices and technical foundations
- Implement experiment tracking and management systems
- Improve data streaming and processing infrastructure
- Manage data versioning, lineage, and reproducibility
- Optimize data loading and I O performance for GPU utilization
- Own infrastructure from architecture through production deployment
- Profile system bottlenecks and optimize training throughput
- Support deployments and customer site visits
Perks/Benefits
- End-to-end responsibility
- Fast-paced startup environment
- High autonomy
- Onsite work
- Ownership
- Remote hiring support
Skills/Tech-stack
Cloud Storage | Compute Orchestration | Computer Vision | Data Lineage | Data Pipelines | Data Versioning | DeepSpeed | Distributed Training | Docker | Experiment tracking | FSDP | GPU clusters | GRPC | I/O | I/O Optimization | Kubernetes | Learning operations | MLflow | Machine Learning | Machine Learning Operations | Multimodal Data | Multimodal Data Pipelines | NVIDIA CUDA | PyTorch | Python | Robotics datasets | Sensor data | Spark | Triton | WandB
Education
Regions
Countries
States
Cities
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