Founding Engineer – ML Demand Generation

• 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.

• 3–10 years of experience in ML engineering, data science, or growth analytics.
• Strong Python proficiency and hands‑on experience with PyTorch or Tensor Flow 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., Hub Spot, Salesforce, Meta/Google Ads APIs).

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.

• Machine Learning Models
• Lead Scoring
• Conversion Prediction
• Demand Generation
• Behavioral Analytics
• Audience Segmentation
• Data-Driven Growth Systems
• User Modeling
• Scoring
• Recommendations

• Collaboration
• Communication

• Hub Spot
• Salesforce
• Meta Ads API
• Google Ads API