Founding Engineer – ML Demand Generation

Clera

Founding Engineer focusing on ML-driven demand generation at a Series A AI/ML platform company. Blending data science and growth strategy to enhance lead generation and marketing effectiveness.

Posted 7/10/2026full-timeMountain View • California • 🇺🇸 United StatesMid-LevelSenior💰 $220,000 - $300,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in building and deploying machine learning models for lead scoring and conversion prediction, alongside designing production data pipelines for behavioral analytics. Proven ability to collaborate with marketing and product teams to drive measurable growth outcomes through data-driven frameworks.

Highest-signal resume keywords

Machine Learning EngineeringPython ProficiencyPyTorch or TensorFlowProduction Data Pipeline DesignMarketing Tech Stack Familiarity

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine Learning ModelsLead ScoringConversion PredictionDemand GenerationBehavioral AnalyticsAudience SegmentationData-Driven Growth SystemsUser ModelingScoringRecommendations

Soft Skills

CollaborationCommunication

Tools & Technologies

HubSpotSalesforceMeta Ads APIGoogle Ads API

Industry Keywords

Growth AnalyticsCampaign Performance OptimizationPersonalized OutreachChannel OptimizationROI Tracking

Tech Stack

Tools & technologies

PythonPyTorchTensorflow

About the role

Key responsibilities & impact

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.

Requirements

What you’ll need

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

Benefits

Comp & perks

Early-stage equity opportunity