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Clera

Founding ML Engineer – Demand Generation

remote (Remote)$220k–$300kfulltimemidAdded today

About this role

A Series A AI company is seeking a Founding ML Engineer to build intelligent demand generation systems that drive user acquisition and retention. You'll develop lead scoring models, behavioral analytics pipelines, and LLM-powered personalization tools while partnering with marketing and product teams to translate growth objectives into measurable ML solutions.

What you'll do

  • Build and deploy ML models for lead scoring, conversion prediction, and campaign performance optimization
  • Automate demand generation workflows end-to-end from audience segmentation to personalized outreach
  • Design and maintain data pipelines for behavioral analytics, audience targeting, and A/B experimentation
  • Partner with marketing and product teams to translate growth objectives into ML solutions
  • Experiment with LLMs, recommendation systems, and generative AI for content creation and personalization
  • Establish data-driven frameworks for channel optimization and ROI tracking across marketing programs

What they're looking for

  • Python and ML frameworks (PyTorch, TensorFlow)
  • Lead scoring and conversion prediction modeling
  • Data pipeline design and behavioral analytics
  • Marketing tech stacks (HubSpot, Salesforce, Google Ads API, Meta Ads API)
  • LLMs and generative AI applications
  • A/B testing and experimentation frameworks
  • Recommendation systems
  • Channel optimization and ROI measurement

Benefits

  • Founding-level equity and early-stage impact opportunity
  • Competitive salary of $220,000–$300,000 per year
  • Collaborative, high-velocity team environment
  • Work on cutting-edge AI applications
  • On-site location in Mountain View, California
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Clera

Clera builds an agentic operating system that automates complex workflows and processes through AI agents, with a platform designed to simplify distributed infrastructure management for developers. The company is hiring Founding Engineers, Customer Engineers, and Product Engineers to develop both backend systems and user-facing interfaces across their AI automation products.

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Likely interview questions

  • Walk us through a lead scoring or conversion prediction model you built—what features were most predictive and how did you validate it?
  • Describe your experience integrating with marketing platforms like HubSpot or Salesforce. What challenges did you encounter and how did you solve them?
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