Remote [Senior/Staff] Machine Learning Engineer - Ad Ecosystems en Haus
Haus · Estados Unidos De América · Remote
- Senior
About Haus
Haus is a marketing science platform that helps brands measure and maximize the business impact of their marketing spend with scientific precision. Over $360B spent annually on paid advertising in the US alone, and the famous quote “half the money I spend on advertising is wasted; the trouble is I don't know which half” still rings true. Haus helps marketers identify which half, and re-allocate it to maximize growth.
Haus was built by a team of former product managers, economists, and engineers from Google, Netflix, Meta, and others to make high-quality decision science accessible to businesses of all sizes. By automating the heavy lifting of experiment design, data processing, and insights generation, we empower our customers to make more profitable, data-driven decisions. We hear our customers frequently rave about our product, for example "we've seen north of 10x ROI on our annual investment in Haus in the first 2 months alone.”
Haus is on a hypergrowth trajectory, well-capitalized, and backed by top-tier VCs including Insight Partners, Baseline Ventures, Haystack, and others. We're honored that Haus has once again been recognized and has made the list for 2025's exceptional startups!
What you'll do:
This role will lead high-impact projects from the ground up. You’ll have the autonomy to design and build systems that could fundamentally reshape the advertising ecosystem. The work will involve developing complex intervention systems, advanced marketing planning tools, and optimization engines powered by machine learning and causal inference.
We’re looking for individuals who thrive on solving tough problems, think critically, and love turning ideas into scalable, production-ready systems. If you enjoy both writing production code and building innovative solutions, this role is for you.
Salary ranges are determined by role and level, and within the range individual pay is determined by additional factors including job-related skills, experience, and relevant education or training. Please note that the compensation details listed in this job posting reflect the base salary only, and do not include equity or benefits.
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What we offer:
Haus is an equal opportunity employer and makes employment decisions without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran status, disability status, age, or any other status protected by law.
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