Founding Engineer - ML Demand Generation
About the Role
This is a founding-level ML engineering role at the intersection of data science and growth strategy, sitting at the core of a fast-moving AI/ML data and services company. You'll build intelligent systems that drive user acquisition, lead conversion, and campaign performance — turning machine learning directly into measurable business impact.
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 data pipelines for behavioral analytics, targeting, and experimentation.
Collaborate with marketing and product teams to translate growth goals into measurable ML 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 experience in demand generation, growth marketing, or data-driven marketing domains.
Strong Python proficiency with practical experience using PyTorch and/or TensorFlow for building and deploying models.
Experience integrating with marketing and CRM platforms (e.g. HubSpot, Salesforce) in ML-driven workflows.
Familiarity with advertising APIs (e.g. Google Ads API, Meta Ads API) for model-driven campaign optimization.
Proven ability to build data pipelines for A/B testing, audience segmentation, and behavioral analytics.
Track record developing solutions for lead scoring, conversion prediction, and performance optimization.
Experience with LLMs, recommender systems, and generative AI techniques.
Strong cross-functional communication skills; comfortable translating growth goals into engineering deliverables.
Bachelor's degree in Computer Science, Engineering, Mathematics, or a related field — or equivalent practical experience.
Compensation & Benefits
Base salary range: $220,000 – $300,000 USD annually. Visa sponsorship is available for this role.
Location
This is a fully on-site role based in Mountain View, California, US.