Machine Learning Engineer, Advertising & Marketing Performance Intelligence
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Looking for a marketing job in Seattle? Choose from 20 open roles at 6 employers. Explore real salary data and skills breakdown across remote, hybrid and on-site roles.
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The bulk of the roles are applied science and machine learning positions embedded within marketing and advertising contexts. Several focus on building agentic AI systems that automate and optimise advertiser campaigns at scale, as seen in the Applied Scientist III, Sponsored Products and Brands and Applied Scientist II postings, which involve multi-agent orchestration, reasoning pipelines, and production code.
Other postings address cross-border seller growth and large-scale ML deployment, including bid optimisation and campaign automation across multiple marketplaces, as described in the cross-border seller experience role and the Sr. Machine Learning Engineer posting.
A smaller number of postings are closer to traditional marketing work. The Sr. Partner Marketing Manager, AI role involves go-to-market strategy, joint campaigns, and partner channel management for AI model providers, requiring marketing experience alongside AI familiarity rather than deep technical credentials.
The skills table reflects mentions in descriptions across all postings, not stated requirements, and the sample is small so patterns should be read cautiously. The frequent appearance of PhD, Python, LLMs, and Master's degree signals that most postings lean toward research and engineering profiles. A/B testing and statistics appear in a minority of postings, suggesting analytical marketing skills matter in some but not all roles.
Every posting on this page is listed as onsite; none are marked hybrid or remote. Candidates should assume in-person attendance is expected in Seattle unless individual postings specify otherwise. No postings state flexible or partial remote arrangements, so it would be worth confirming current working arrangements directly with each employer, as onsite designations in job postings do not always reflect day-to-day practice once a candidate is in role.
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