Software Engineer, Machine Learning - Ads Products
Menlo Park, CAJob$184–257K/yrSeen todaySeen in employer's feed today
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Job overview
Meta’s Ads organization builds advertiser-facing campaign, optimization, measurement, payment, and business-management products. The Software Engineer, Machine Learning in Ads Products leads complex engineering projects that turn ML capabilities into useful advertiser products. The role develops and integrates models for campaign optimization and advertiser experiences, working with product, data science, and engineering teams to define success, evaluate improvements, and deliver reliable capabilities that improve advertising results.
Skills & qualifications
Skills
Qualifications
Full job description
Summary:
Meta's Ads organization builds the systems that help businesses of every size reach the people most likely to care about what they offer. At our core, we're builders who care about shipping real value. We own the advertiser-facing side of that work, end to end: the campaign and optimization products that drive advertiser results; the business experiences where advertisers plan, create, and manage their work, from a first boosted post to a global agency's workflow; the signals, attribution, and measurement that prove what their advertising delivered; and the payments and financial systems the money moves through, along with the integrity work that keeps them trusted. AI is changing all of it - what we build for advertisers and how we build it - and ours is the org where advertiser value is won or lost.As a Software Engineer, Machine Learning in Ads Products, you will lead complex engineering projects that turn ML capabilities into useful advertiser products. You will develop and integrate models for campaign optimization and advertiser experiences, partnering with product, data science, and engineering teams to define success, evaluate improvements, and deliver reliable capabilities that help businesses achieve better advertising results.
Required Skills:
Software Engineer, Machine Learning - Ads Products Responsibilities:
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Define and deliver ML-powered product capabilities for campaign optimization or advertiser experiences, from technical design through launch and iteration.
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Translate advertiser and product needs into model objectives, evaluation methods, and maintainable production software.
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Use data and analysis to diagnose model and product behavior, compare technical approaches, and guide engineering decisions.
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Partner with product, data science, and engineering teams to design experiments and assess advertiser outcomes.
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Lead cross-functional execution across model, data, service, and product integration dependencies for complex projects.
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Improve model and product quality through testing, rollout controls, monitoring, and production feedback.
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Mentor engineers in ML product design, evaluation, and reliable delivery.
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Help teammates ramp up across the model, data, service, and product codebases.
Minimum Qualifications:
Minimum Qualifications:
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Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
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8+ years of programming experience in a relevant language OR 4+ years experience with a PhD
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Demonstrated experience driving change within an organization and leading complex technical projects
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Experience utilizing data and analysis to explain technical problems and provide detailed feedback and solutions
Preferred Qualifications:
Preferred Qualifications:
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Experience with privacy-preserving measurement and modeling under signal loss (e.g. aggregated/delayed conversion signals)
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Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)
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Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)
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Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies
Public Compensation:
$183,997/year to $257,000/year + bonus + equity + benefits
Industry: Internet
Equal Opportunity:
Meta is proud to be an Equal Employment Opportunity and Affirmative Action employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereotypes, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state and local law. Meta participates in the E-Verify program in certain locations, as required by law. Please note that Meta may leverage artificial intelligence and machine learning technologies in connection with applications for employment.
Meta is committed to providing reasonable accommodations for candidates with disabilities in our recruiting process. If you need any assistance or accommodations due to a disability, please let us know at [email protected].
How this job compares
Set against the 41,748 open Software Engineer jobs on Olive Jobs, counted November 8, 2026.
- Pay
- This posting$184–257K/yr
- California median$165–249K/yr7,714 salary ranges
- US median$135–219K/yr33,246 salary ranges
This range's midpoint, $220K, is 8% above the California median midpoint ($205K) — in the middle half of Software Engineer salary ranges in California.
- Openings
- Olive Jobs lists 9,625 open Software Engineer jobs in California and 41,748 across the US. 8% of them nationwide are listed as remote or flexible.
- Experience
- This posting asks for at least 4 years of experience; Software Engineer postings that state a minimum ask for 5 years at the median (34,144 postings).
- Education
- 13,035 of the 41,748 open Software Engineer jobs (31%) ask for a bachelor's degree or higher.
Counted across the open, public US postings on Olive Jobs on November 8, 2026. Pay medians are the middle values of the low ends and of the high ends of postings that list both ends of a range in the same cadence (a yearly salary or an hourly rate); a range's midpoint is halfway between its ends. Pay and experience figures resting on fewer than 20 postings are left out.
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