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Hiring Tech · Classical ML · Founder-Led Product

Grownout

AI Hiring Platform from First Commit to Exit

Co-founded, architected, and scaled an AI-powered hiring platform from the first line of code to strategic acquisition in under four years.

Grownout

Scope & Responsibilities

  • •Led commercial product vision and technical architecture end-to-end
  • •Built classical ML pipeline from feature engineering to production
  • •Drove enterprise workflow redesign around AI candidate matching
  • •Ran iterative model and UX experiments on live customer behavior
  • •Scaled platform execution from concept to enterprise adoption

Key Features

  • •Real-time candidate ranking and matching system
  • •AI-assisted enterprise screening workflow automation
  • •Data-driven optimization loops across product and ML outputs
  • •Enterprise onboarding and hiring pipeline acceleration

Technology Highlights

  • •Python
  • •MongoDB

Technical Considerations

  • •Model quality and explainability in high-stakes hiring decisions
  • •Tight integration of ML outputs into recruiter workflows
  • •Balancing speed of iteration with enterprise reliability needs

Outcome

Secured two Indian patents, reduced average time-to-hire by 70% (35 to 10 days), and improved sourcing cycle speed by 40% ahead of acquisition.