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.