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Diagon favicon
Diagon

Senior Autonomous Data Systems Engineer

Streamline CAPEX procurement by using AI to match technical specifications with industrial equipment from over 32,000 verified global manufacturing suppliers.

engineeringhybridSF Bay Area, USfull-time

Benefits:

  • Full ownership

  • Freedom to choose tools and patterns

  • Small, focused, AI-augmented team environment

  • Opportunity to shape the future of manufacturing data at planetary scale

Experience Requirements:

  • 5+ years in software engineering, ideally with standalone service builds

  • Experience with building scalable schemas and ingestion

  • Strong background in web scraping/data pipelines (ETL, Airflow, similar)

  • Demonstrated expertise in using AI tools/workflows to accelerate development responsibly

  • A mix of technical depth, curiosity, and the ability to go deep or pivot quickly

Other Requirements:

  • Excellent communication, autonomy, and a growth mindset

  • Experience in manufacturing tech, marketplaces or hardware sourcing

  • Experience with a Next.js, Tailwind and PostgreSQL stack

  • Familiarity with web scraping at scale

Responsibilities:

  • Lead AI-powered data warehousing of manufacturing equipment information

  • Architect a data store to represent (almost) every product and OEM globally

  • Build ingestion pipelines from internal and external sources

  • Develop internal web UIs for data review & curation

  • Expose clean APIs for other services to sync with and build from

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Ambient.ai

Senior Software Engineer, AI Infra

Transform reactive video monitoring into proactive prevention using AI-powered vision intelligence that detects threats and reduces false alarms in real time.

engineeringhybridSF Bay Area, US
$168K - $210K
full-time

Benefits:

  • Stock options

  • Comprehensive health + welfare package

  • Flexible time off

  • Winter Break

  • Latest tech and awesome swag

Education Requirements:

  • BS/MS in Computer Science or related field

Experience Requirements:

  • 4+ years of industry experience

  • Strong background in machine learning and deep learning

  • Proficient in designing and building scalable ML infrastructure

  • Expertise in Python

  • Experience with data engines for management of training data

Other Requirements:

  • Background in computer vision is a strong plus

  • Experience with LLMs, LVMs, and RAG into production is a strong plus

Responsibilities:

  • Building and maintaining machine-learning infrastructure

  • Develop a robust data engine for training data

  • Collaborate with research scientists to integrate advancements

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