Research Engineer - Large-Scale AI Models & Pipelines

Magic; San Francisco (CA); On-site; USD 120,000 - 160,000; Full time

Job summary

Magic is seeking a Research Engineer in San Francisco to train, evaluate, and serve large AI models while optimizing inference throughput for novel architectures. You will build and curate large-scale datasets and contribute to transformative product ideas.

The ideal candidate should have strong software engineering skills and thorough knowledge of deep learning literature, with experience working on large distributed systems.

Qualifications

• Strong general software engineering skills.
• Thorough knowledge of the deep learning literature.
• Experience with pre- and post-training of LLMs.
• Ability to come up with and evaluate research ideas.
• Experience working with large distributed systems.
• Ability to handle large ETL workloads.

Responsibilities

• Train, evaluate, and serve large AI models.
• Optimize inference throughput for novel model architectures.
• Contribute to frameworks for research and production.
• Train trillion-parameter models on large GPU clusters.
• Curate post-training datasets to improve capabilities.
• Build internet-scale data pipelines and crawlers.
• Design and prototype new model architectures.

Skills

Software engineering skills

Deep learning knowledge

Experience with LLMs

Research evaluation skills

Large distributed systems experience

ETL workload handling

Job description

Magic is seeking a Research Engineer in San Francisco to train, evaluate, and serve large AI models while optimizing inference throughput for novel architectures. You will build and curate large-scale datasets and contribute to transformative product ideas.

The ideal candidate should have strong software engineering skills and thorough knowledge of deep learning literature, with experience working on large distributed systems.