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
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Build ML models to optimize lead scoring, conversion prediction, and campaign performance.
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Automate demand generation workflows, from audience segmentation to personalized outreach.
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Design data pipelines for behavioral analytics, targeting, and experimentation.
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Collaborate with marketing and product teams to translate growth goals into measurable ML solutions.
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Experiment with LLMs, recommendation systems, and generative AI for content and outreach.
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Establish data-driven frameworks for channel optimization and ROI tracking.
What We're Looking For
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3–10 years of hands-on ML engineering experience in demand generation, growth marketing, or data-driven marketing domains.
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Strong Python proficiency with practical experience using PyTorch and/or TensorFlow for building and deploying models.
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Experience integrating with marketing and CRM platforms (e.g. HubSpot, Salesforce) in ML-driven workflows.
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Familiarity with advertising APIs (e.g. Google Ads API, Meta Ads API) for model-driven campaign optimization.
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Proven ability to build data pipelines for A/B testing, audience segmentation, and behavioral analytics.
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Track record developing solutions for lead scoring, conversion prediction, and performance optimization.
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Experience with LLMs, recommender systems, and generative AI techniques.
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Strong cross-functional communication skills; comfortable translating growth goals into engineering deliverables.
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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.
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