Director, Evaluation and Quality Assurance, Services Special Projects

Apple, Inc.; Cupertino (CA); On-site; USD 311,000 - 497,000; Full time

Benefits offered by this job

Apple stock programs

Discretionary bonuses or commission

Discretionary employee stock purchase

Comprehensive medical and dental

Retirement benefits

Relocation assistance

Job summary

Apple in Cupertino, CA seeks a Director to build and lead the evaluation and quality assurance function for a major multi-year engineering initiative. You will define end-to-end quality, create scale-ready evaluation infrastructure, and recruit the team, tooling, and operating rhythm needed to catch issues before users are affected.

You will partner with engineering, applied ML, and program management leadership, setting strategy and direction with latitude in an area with no existing

Qualifications

• 12+ years of experience in data science, machine learning evaluation, quality assurance, or test engineering roles in a technical product environment, including experience building and leading multi-level QA or evaluation organizations through managers.
• Demonstrated experience building an evaluation or QA function from the ground up — defining metrics, process, tooling, and organizational structure where none previously existed.
• Extensive experience utilizing LLM-based autograders and rubrics, including rubric design, evaluation set development, validation, calibration, and human-model alignment, and using them to proactively drive product and model improvements.
• Deep experience in traditional human evaluation methodology, logging, and A/B testing for consumer-facing products at scale.
• Experience evaluating conversational AI, recommendation, ranking, or search systems, and — ideally — agentic or tool-use systems that take real-world actions, not just generate responses.
• BS in Computer Science, Engineering, or a related technical field, or equivalent experience.
• Experience with quality assurance for third-party API integrations.
• Experience with logging infrastructure and instrumentation for AI product quality measurement.
• Exceptional written and verbal communication skills, with a track record of presenting quality status, risk, and trade-offs clearly to, and influencing decisions among, senior executive leadership.

Responsibilities

• Design metrics and automated grading systems ("autograders") that scale to large, frequently changing datasets, utilizing those alongside human evaluation, and determining where the line between those should sit.
• Wiring evaluation results into release processes as explicit quality gates, not just after-the-fact reporting.
• Catching and preventing quality regressions across an entire product surface — from user-facing correctness to backend transaction integrity.
• Partnering with engineering and applied ML teams to define what "quality" and "done" mean before a product's own definitions of those things have settled.
• Navigating ambiguity and building structure — process, tooling, org design — in an environment where none of it exists yet.
• Making judgment calls under uncertainty about where to invest limited evaluation resources for maximum risk reduction.

Skills

Data science

Machine learning evaluation

Quality assurance

Test engineering

Leadership

Education

BS in Computer Science or Engineering

Tools

LLM-based autograders

A/B testing tooling

Job description

Director, Evaluation and Quality Assurance, Services Special Projects

Cupertino, California, United States Software and Services

We are looking for a Director to build and lead the evaluation and quality assurance function for one of our most ambitious multi-year engineering initiatives. This is a true 0-to-1, first-key-hire role: There is no existing team, tooling, or process to inherit. You will define how we measure quality across an entire product end to end, build the automation and evaluation infrastructure to do it at scale (or borrow other teams' infrastructure), and build and lead the organization that runs it.

Description

You will own evaluation and quality assurance for every layer of the product — from whether the system is being correctly triggered for the right set of user requests, through whether it surfaces and ranks the right results, to whether the underlying transactions execute correctly, including integrations with external partner APIs, and financial systems. Quality here isn't a single test suite — it spans conversational understanding, relevance and ranking, and revenue-bearingcorrectness, all against a large, constantly evolving real-world dataset.You will create and drive the evaluation and quality strategy and implementation for the product. This will extensively utilize automated grading systems and human evaluation programs where appropriate. You will make the calls about where to invest in each. You will define what "correct" and "good" mean for this product, wire that definition into continuous, always-on evaluation pipelines with clear pass/fail quality gates tied to releases, and build the team, tooling, and operating rhythm to catch issues before they reach users.As the first hire in this space, you will operate with significant latitude and ambiguity — setting strategy, process, and technical direction with minimal existing scaffolding, while also building and scaling an organization. You will partner closely with engineering, applied ML, and program management leadership, including senior executive stakeholders, and you will be a key voice in defining what "quality" and "done" mean for a product still taking shape, as well as iterating on decision points in production after the product ships.

Responsibilities

• Design metrics and automated grading systems ("autograders") that scale to large, frequently changing datasets, utilizing those alongside human evaluation, and determining where the line between those should sit.
• Wiring evaluation results into release processes as explicit quality gates, not just after-the-fact reporting.
• Catching and preventing quality regressions across an entire product surface — from user-facing correctness to backend transaction integrity.
• Partnering with engineering and applied ML teams to define what "quality" and "done" mean before a product's own definitions of those things have settled.
• Navigating ambiguity and building structure — process, tooling, org design — in an environment where none of it exists yet.
• Making judgment calls under uncertainty about where to invest limited evaluation resources for maximum risk reduction.

Minimum Qualifications

• 12+ years of experience in data science, machine learning evaluation, quality assurance, or test engineering roles in a technical product environment, including experience building and leading multi-level QA or evaluation organizations through managers.
• Demonstrated experience building an evaluation or QA function from the ground up — defining metrics, process, tooling, and organizational structure where none previously existed.
• Extensive experience utilizing LLM-based autograders and rubrics, including rubric design, evaluation set development, validation, calibration, and human-model alignment, and using them to proactively drive product and model improvements.
• Deep experience in traditional human evaluation methodology, logging, and A/B testing for consumer-facing products at scale.
• Experience evaluating conversational AI, recommendation, ranking, or search systems, and — ideally — agentic or tool-use systems that take real-world actions, not just generate responses.
• BS in Computer Science, Engineering, or a related technical field, or equivalent experience.
• Experience with quality assurance for third-party API integrations.
• Experience with logging infrastructure and instrumentation for AI product quality measurement.
• Exceptional written and verbal communication skills, with a track record of presenting quality status, risk, and trade-offs clearly to, and influencing decisions among, senior executive leadership.

Preferred Qualifications

• 15+ years of experience in data science, machine learning evaluation, quality assurance, or test engineering roles in a technical product environment, including experience building and leading multi-level QA or evaluation organizations through managers.

At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $311,100 and $496,900, and your base pay will depend on your skills, qualifications, experience, and location.

Benefits

• Apple employees also have the opportunity to become an Apple shareholder through participation in Apple’s discretionary employee stock programs.
• Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple’s Employee Stock Purchase Plan.
• Comprehensive medical and dental coverage
• Retirement benefits
• A range of discounted products and free services
• Reimbursement for certain educational expenses — including tuition
• Discretionary bonuses or commission payments
• Relocation assistance

Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.

Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant

At Apple, we believe accessibility is a fundamental human right. You’ll find that idea reflected in everything here — in our culture, our benefits and our digital tools. By welcoming as many perspectives as possible, we help you build a career where you feel like you belong.

Learn about accessibility in Apple’s workplace

Learn about reasonable accommodations for job applicants

Apple accepts applications to this posting on an ongoing basis.