Founding Engineer - ML Demand Generation.

About the Role

This is a founding-level ML engineering role at an AI/ML data and services company, sitting at the intersection of machine learning and growth. You'll build intelligent systems that directly drive user acquisition, engagement, and revenue — turning data science into measurable demand outcomes.

What You'll Do

• Build ML models to optimize lead scoring, conversion prediction, and campaign performance.

• Automate demand generation workflows, from audience segmentation to personalized outreach.

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

• Partner with marketing and product teams to translate growth goals into ML-driven solutions.

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

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

What We're Looking For

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

• Strong Python skills with practical experience in PyTorch and/or TensorFlow for building and deploying models.

• Proven track record with data-driven growth systems: lead scoring, conversion prediction, user modeling, or campaign optimization.

• Experience integrating with marketing and CRM platforms (e.g. HubSpot, Salesforce) in ML-driven workflows.

• Familiarity with advertising APIs (e.g. Google Ads, Meta Ads) for model-driven campaign optimization.

• Experience with LLMs, recommender systems, and generative AI techniques.

• Strong cross-functional communication skills to bridge technical and growth teams.

• Bachelor's degree in Computer Science, Engineering, Mathematics, or a related field — or equivalent practical experience.

Compensation & Benefits

Base salary: $220,000 – $300,000 USD annually. Visa sponsorship is available for this role.

Location

On-site, full-time in Mountain View, California, USA. Remote work is not available for this position.