Founding ML Engineer – Demand Generation

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

• 3–10 years of hands‑on ML engineering, data science, or growth analytics experience.
• Direct exposure to demand generation, lead scoring, or campaign optimization in a production environment.
• Strong proficiency in Python and ML frameworks (PyTorch, Tensor Flow).
• Proven experience building and deploying data pipelines for behavioral analytics, segmentation, and experimentation.
• Hands‑on experience with marketing technology and APIs:
  Hub Spot, Salesforce, Google Ads API, Meta Ads API.
• Experience experimenting with LLMs, recommendation systems, or generative AI for content and outreach.
• A builder's mindset — you move fast, experiment often, and own measurable outcomes.
• Must be authorized to work in the United States without employer sponsorship.

Demonstrates expertise in building and deploying ML models for lead scoring and campaign optimization, with strong proficiency in Python and ML frameworks. Proven ability to design data pipelines and automate demand generation workflows while collaborating cross‑functionally to achieve growth objectives.