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
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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 and maintain data pipelines for behavioral analytics, targeting, and experimentation.
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Partner with marketing and product teams to translate growth goals into ML-driven 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, data science, or growth analytics experience.
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Strong Python skills with practical experience in PyTorch and/or TensorFlow for building and deploying models.
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Proven track record with data-driven growth systems: lead scoring, conversion prediction, user modeling, or campaign optimization.
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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, Meta Ads) for model-driven campaign optimization.
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Experience with LLMs, recommender systems, and generative AI techniques.
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Strong cross-functional communication skills to bridge technical and growth teams.
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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.