For our client, we are seeking a Sr. Staff Machine Learning Engineer Agentic Ads to join the team of a leader in the Consumer Technology space. This role will lead work at the intersection of data, AI‑enabled capabilities, and scalable technology delivery. You will work across engineering, product, operations, and business stakeholders to translate complex requirements into practical technology solutions. The position offers the opportunity to influence architecture, execution quality, and the technology capabilities that enable long‑term growth within a technology‑driven environment. Location: San Francisco, CA – US based candidates only, no visa sponsorship available. Compensation: $227,871 – $469,147 annually.
Responsibilities
- Lead technical strategy for improving ads ranking and bidding models using large‑scale ML
- Design, build, and launch production models that enhance ad quality and relevance
- Develop and refine training and feedback pipelines that learn from real‑world data
- Utilize AI to expedite analysis while ensuring model quality and accuracy
- Shape modeling roadmaps by partnering closely with product and engineering teams
- Drive technical design reviews and establish best practices for modeling
- Mentor other MLEs and scientists in advanced modeling techniques and workflows
Qualifications
- Minimum of 8 years of experience in applied machine learning related to large‑scale ranking or advertising systems
- Deep expertise in modern recommendation and ranking techniques including gradient boosted trees and deep learning
- Proficiency in building and operating ML systems at scale using Python or C++ and modern data platforms
- Demonstrated ability to leverage AI to enhance modeling and analysis workflows
- Proven experience in leading cross‑functional initiatives and influencing senior stakeholders
- Bachelor's/Master's degree in computer science, statistics, or a related field, or equivalent experience
- High integrity in data handling, ensuring responsible use of AI and accountability
Benefits
- In‑office collaboration required 1‑2 times per month at designated locations (Seattle, San Francisco, Palo Alto, Los Angeles)
- Work in a supportive environment that prioritizes equity and inclusion
- Access to the company’s rich multimodal data and modern ML infrastructure for innovative experiments
Our client is an equal opportunity employer. We encourage you to apply even if you don’t meet every qualification—your background could be exactly what this team needs.
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