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Staff Software Engineer, Data Platform

Scale AI · San Francisco, CA; New York, NY · New York, NY · San Francisco, CA

Infrastructureonsitestaff
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At a glance

Highlights

  • Lead core data platforms powering the world's most advanced LLMs.
  • Build systems behind Generative AI Data Engine, SGP and Donovan.
  • Gain front-row exposure to AI work across startups and governments.

What they offer

  • base salary
  • equity
  • benefits

Ideal candidate

Seasoned backend leader who loves owning large-scale data systems end-to-end, mentoring engineers, and translating complexity into clarity to advance cutting-edge AI.

Requirements

  • 8+ years of full-time post-graduation engineering experience in back-end systems building large-scale data storage, streaming and warehousing systems
  • Extensive experience in database technologies (MongoDB, Postgres), streaming/processing (Kinesis, Flink, Spark), indexing/caching (ElasticSearch, Redis) and query engines (Trino, Presto, Snowflake)
  • Track record of mentoring and leading teams in successful projects
  • Excellent communication and collaboration skills with ability to translate complex concepts for non-technical stakeholders
  • Experience with containerization and deployment technologies like Kubernetes and public cloud offerings
  • Deep understanding of distributed systems, cloud platforms and data systems
  • Experience driving cross-functional collaboration and communication at organizational level

Lab profile

About Scale AI

AI data foundry providing high-quality data for training, fine-tuning, and evaluating AI systems.

What they build

  • Training, fine-tuning, and evaluation data for frontier models
  • Multimodal and coding data for audio, image, video and world models
  • Custom AI applications for enterprise and global public sector

Known for

  • Leading data partner for frontier model developers
  • Trusted across enterprise, defense and public sector
  • Depth in multimodal, coding and physical AI
  • End-to-end capability from strategy to delivery and evaluation

Key facts

  • Founded in 2016
  • Headquartered in San Francisco, California
  • Private company backed by Accel, Founders Fund, Index Ventures, Nvidia and Meta
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