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Founding Engineer – ML Demand Generation

Role overview

Qualifications

  • 3–10 years of experience in ML engineering, data science, or growth analytics
  • Strong Python proficiency and hands-on experience with PyTorch or TensorFlow and end-to-end ML pipelines
  • Proven track record building ML models for lead scoring, conversion prediction, or demand generation outcomes
  • Experience designing production data pipelines for behavioral analytics, audience segmentation, and experimentation

Responsibilities

  • Build and deploy ML models for lead scoring, conversion prediction, and campaign performance optimization
  • Automate demand generation workflows spanning audience segmentation and personalized outreach
  • Design and maintain production data pipelines for behavioral analytics, targeting, and experimentation
  • Partner closely with marketing and product teams to translate growth goals into measurable ML solutions

About the company

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Clera

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Company details

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Job description

About the Role

A well-funded Series A AI/ML platform company is looking for a Founding Engineer focused on ML-driven demand generation to join their on-site team in Mountain View, CA. This is a high-impact, early-stage role where you will blend data science, machine learning, and growth strategy to build intelligent systems that power lead generation, personalization, and performance marketing — directly shaping acquisition, conversion, and retention outcomes.

What You'll Do

  • Build and deploy ML models for lead scoring, conversion prediction, and campaign performance optimization.

  • Automate demand generation workflows spanning audience segmentation and personalized outreach.

  • Design and maintain production data pipelines for behavioral analytics, targeting, and experimentation.

  • Partner closely with marketing and product teams to translate growth goals into measurable ML solutions.

  • Experiment with LLMs, recommendation systems, and generative AI for content personalization and outreach.

  • Establish data-driven frameworks for channel optimization and ROI tracking.

What We're Looking For

Must-haves:

  • 3–10 years of experience in ML engineering, data science, or growth analytics.

  • Strong Python proficiency and hands-on experience with PyTorch or TensorFlow and end-to-end ML pipelines.

  • Proven track record building ML models for lead scoring, conversion prediction, or demand generation outcomes.

  • Experience designing production data pipelines for behavioral analytics, audience segmentation, and experimentation.

  • History of collaborating with marketing and product teams to deliver measurable growth outcomes.

  • Experience with data-driven growth systems such as user modeling, scoring, recommendations, or automation.

Nice to have:

  • Familiarity with marketing tech stacks and ad platforms (e.g., HubSpot, Salesforce, Meta/Google Ads APIs).

  • Experimentation with LLMs, recommender systems, or generative AI for content and outreach.

The right mindset: You move fast, iterate quickly, own measurable impact, and are genuinely curious about how AI techniques can drive real business outcomes.

Compensation & Benefits

  • Salary: $220,000 – $300,000 USD annually

  • Early-stage equity opportunity

  • On-site role in Mountain View, CA

Visa sponsorship is not available for this role.

Location

This is a fully on-site position based in Mountain View, California. Candidates must be available to work on-site; remote or visa-requiring applicants will not be considered.

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MR

Marcus Rivera

Chief Revenue Officer

m.rivera@company.com
linkedin.com/in/marcusrivera
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