About the RoleThis 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 & BenefitsBase salary range:
$220,000 - $300,000 USD annually. Visa sponsorship is available for this role.
LocationThis is a fully
on-site role based in
Mountain View, California, US.
