QA Engineering Lead, AI Native

Benefits

Parental leave

Not verified

Non-birth-parent leave

Not verified

Family-building benefits

• Fertility benefits: Not verified
• Adoption assistance: Not verified
• Surrogacy assistance: Not verified

Mental health support

Not verified

Relocation assistance

Not verified

Childcare support

Not verified

Learning budget

Not verified

Verification

Not verified checked Jun 7, 2026

Salary

$138K-$191K From the posting source

401(k) match

Reported from DOL Form 5500 industry filing (not employer-specific)

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Market context

U.S. role benchmark (BLS OEWS)

$111,944 U.S. median for this role

Projected growth (BLS Employment Projections)

+13.7% - Much faster than average

47% above the BLS role benchmark for data and ml aggregate.

Matched to SOC 15-1252 - Data and ML aggregate by role bucket.

Source: U.S. Bureau of Labor Statistics, OEWS, May 2024 and Employment Projections, 2024-2034.

Role

Role function

Data From the posting source

Seniority

Senior From the posting source

Schedule

Shift type

Not verified

Weekend work

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Company

Equity

Offered Verified - SEC 10-K source

Application

Cover letter

Not verified

Assessment

Not verified

Deadline

Not stated

Where they hire

State eligibility is not yet verified.

About this role

QA Engineering Lead, AI Native Menlo Park, CA Meta is seeking a QA Engineering Lead with expertise in AI product and model testing to drive the quality vision for our next-generation AI-powered products. In this role, you will lead the design and execution of comprehensive test strategies for AI models spanning text, image, and voice, ensuring our solutions are robust, reliable, and ethically sound. You will work on products built with cutting-edge technology, serving billions of users worldwide, and play a pivotal role in shaping the future of AI quality at Meta. Responsibilities: - Build and foster a quality-driven engineering environment that enables rapid, confident product releases, ensuring that quality is embedded throughout the development lifecycle - Develop and implement robust evaluation processes for AI models, including prompt engineering, scenario-based, and adversarial testing for text, image, and voice AI systems - Drive the quality for products and features, assess risks, and ensure features ship with a high quality bar, balancing speed and experience - Plan, develop, and execute comprehensive test strategies across core Meta products and platforms, leveraging both manual and automated approaches - Lead quality assurance efforts that align with product objectives, developing scalable solutions to support rapid product iteration and deployment - Solve cross-platform engineering challenges and contribute impactful ideas to improve quality, reliability, and user experience across diverse product surfaces - Implement and evolve QA processes to obtain effective test signals and scale testing efforts across multiple products, ensuring continuous improvement - Define quality metrics and implement

Read the full description at www.metacareers.com. FewerJobs shows a preview and links to the original posting.