Research Scientist Intern (AI Infrastructure)- 2026 Start (PhD)
San Jose, California, United States
USD 156K-316K (estimate) Entry-level Internship
Tasks
- Architect ETL and data ingestion pipelines
- Build distributed training and serving systems
- Collaborate with ML researchers on production systems
- Design scalable AI infrastructure
- Develop telemetry and benchmarking frameworks
- Ensure fault tolerance and high availability
- Implement auto scaling across data centers
- Implement containerized service architectures
- Integrate experiment management and workflow orchestration
- Mentor engineers on systems design and reliability
- Optimize ML stack performance
Perks/Benefits
- Collaboration with industry experts
- Community building
- Development workshops
- Mentorship
- Social events
Skills/Tech-stack
Apache Airflow | Apache Beam | Apache Spark | Artificial Intelligence | Auto Scaling | Benchmarking | Containerization | Dask | Data Ingestion | Data Pipelines | Data Preprocessing | Data Processing | Distributed Systems | ETL | Experiment Management | Fault Tolerance | Flume | GPU scheduling | High Availability | Inference frameworks | Infrastructure architecture | Kubeflow | Kubernetes | Machine Learning | Machine learning compiler | Metaflow | NCCL | RDMA | Resource Management | Scalable systems | Service Oriented | Service-Oriented Architecture | TPU Scheduling | Telemetry | Training frameworks | Unikernels | Virtual Machines | Workload placement
Education
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