Saturday Ads Quality Rater Jobs (NOW HIRING)

At Apple, we focus deeply on our customers’ experience. Apple Ads brings this same approach to advertising, helping people find exactly what they’re looking for and helping advertisers grow their businesses.
Our technology powers ads and sponsorships across Apple Services, including the App Store, Apple News, and MLS Season Pass. Everything we do is designed for trust, connection, and impact: We respect user privacy, integrate advertising thoughtfully into the experience, and deliver value for advertisers of all sizes-from small app developers to big, global brands. Because when advertising is done right, it benefits everyone.
Description
We are looking for a leader with deep experience in Ad Tech who has built and scaled complex machine learning models in production. Preferably, you have a strong track record of delivering high-impact response prediction systems (e.g., click-through rate, conversion rate, post-conversion optimization) at scale, and understand the nuances of optimizing for user engagement, relevance, and long-term value under latency constraints.
You bring hands-on experience developing and deploying large-scale models, with an appetite for pushing state-of-the-art techniques and advancing model capability through increased scale and complexity. You are motivated by privacy-preserving machine learning and have experience building systems that operate effectively within privacy-first constraints.
In this role, you will lead the strategy and development of inference models that predict and optimize user interactions with ads, working across the full modeling stack-from data and model training pipelines to real-time serving and experimentation. You will partner closely with engineering and product teams to define and execute a forward-looking roadmap. You thrive in a fast-paced, Agile environment and are a hands-on ML leader who can drive execution while building strong, collaborative teams.","responsibilities":"Lead and grow a high-performing, team of ML engineers and applied scientists focused on Ads Response Predictions across different surfaces
Partner cross-functionally with Engineering, Product and Sales teams to deliver end-to-end solutions from ideation to production
Collaborate closely with platform and infrastructure teams to optimize training, inference, and resource utilization for large-scale ML workloads
Drive development and deployment of state-of-the-art machine learning models (including large-scale neural networks and LLM-based systems) for ads quality and marketplace optimization
Own the full lifecycle of ML systems-data, modeling, offline evaluation, online experimentation, and productionization at scale
Lead A/B experimentation strategy and decision-making, translating complex data insights into clear product and business recommendations
Ensure robust system design across modeling, feature pipelines, and online serving, with a focus on scalability, latency, and reliability
Champion privacy-preserving machine learning approaches in model development, data usage, and system design
Set a high bar for technical excellence, code quality, and operational rigor, including monitoring, debugging, and continuous improvement of production systems
Mentor and develop team members, actively managing performance and fostering a culture of ownership, innovation, and execution
Communicate effectively with senior leadership, distilling complex technical concepts into clear, actionable insights and strategy
Preferred Qualifications
10+ years applying and leading teams that apply advanced statistical/ML methods and work with large, complex data setsPhD in AI/ML/Mathematics/CS or related field
Minimum Qualifications
10+ years applying and leading teams that apply advanced statistical/ML methods and work with large, complex data sets
You can actively participate in investigations into multiple streams of ads quality data, and draw conclusions from data, recommend actions
You have experience in some of the following domains: Algorithms, Architecture, Artificial Intelligence, Database Systems, Data Mining, Distributed Systems, Machine Learning, Networking, Statistics, Game Theory, Auction Design, or other experience with rigorous Quantitative Analysis or Systems Software implementation
Practical understanding of the mathematics behind modern machine learning, linear algebra and statistics
You have experience developing and leading teams who develop in Python or Java
You are familiar with databases, SQL, and scripting languages
Proven ability to take requirements from design through to implementation both independently and with larger teams
You thrive working closely with operational teams on deployment, monitoring, and management concerns
You actively manage performance of the team reporting to you and take responsibility to drive its outcome
PhD or MS in AI/ML/Mathematics/CS or related field
Pay & Benefits
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 $228,100 and $393,800, and your base pay will depend on your skills, qualifications, experience, and location.
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. You'll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses - including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits
Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.