{"schemaVersion":"jobsearcher.job.v1","id":"1148ec15ba507bfc6464ec2b","url":"https://jobsearcher.com/jobs/1148ec15ba507bfc6464ec2b","canonicalUrl":"https://jobsearcher.com/jobs/1148ec15ba507bfc6464ec2b","title":"Software Engineer - Generative Data Platform, Evaluation","description":"Software Engineer - Generative Data Platform, EvaluationSan Francisco, California, United States Software and Services\r\nApple's machine learning features are only as good as the data behind them, and our team builds the platform that lets teams create data that fills the gaps real-world collection can't, provides privacy-preserving ways to train and evaluate our models safely, and helps us ensure our products have seen diverse inputs to generalize properly across the many parts of the world where we operate.In the AI & Machine Learning (AIML) organization, our team builds the self-service tools and platform that turn ideas, text, and images into large-scale generated datasets. We don't produce the datasets ourselves: ML engineers, data scientists, designers, feature teams, ML data operations teams, and Safety and Responsible AI teams across Apple use our platform to generate their own. That data is only valuable if it matches the real world closely enough to train on and to evaluate against, proving our models and features meet Apple's quality bar before they reach customers. As a software engineer on the platform, you'll sit between that technology and the people who depend on it: understanding what they want to create, building the features that make it possible, and helping them get the most from generative AI. It's a hands-on engineering role for someone who enjoys the people side as much as the code.\r\nDescriptionYou'll spend your days moving between engineering and partnership. Synthetic data here does far more than fill gaps: it lets teams build privacy-preserving digital humans, represent locales and domains that real-world collection underserves, and experiment in days instead of waiting on slow, costly data collection. It also gives Safety and Responsible AI red teams the data they need to stress-test models against misuse and edge cases. One day you might be integrating a new image or video generation model and tuning how it runs on GPUs; the next, you might be helping a design team get their first dataset running on the platform, or working with a feature team on model ablations that measure what synthetic data adds to training and evaluation.You'll help teams understand where synthetic data differs from the real data their models see, whether that's how images look or subtler differences in metadata, distributions, and labels, and then build what closes those gaps. Your core partners are ML engineers and data scientists, but you'll also work with designers, artists, and others who are newer to machine learning, and help make these systems understandable and approachable for them. You'll own features end to end, from shaping the request with partner teams to validating the result on production infrastructure.Our team builds with AI coding agents every day, and you'll help shape how we use them well. You don't need a research background in generative models; you'll learn the models on the job. What matters most is strong engineering judgment and the ability to bring people along.\r\nResponsibilitiesPartner with ML engineers, data scientists, and designers to turn their needs into platform features.\r\nSupport teams as they build their own datasets on the platform, and help design model ablations that measure how synthetic data affects training and evaluation.\r\nExplain how ML, vision, and generative models behave to people new to them, including cost, quality, speed, and feasibility.\r\nAssess the domain gap between synthetic and real data, covering visual properties and non-visual ones such as metadata, value distributions, and labels.\r\nWork with feature teams to find where synthetic data falls short for their use case, and build platform capabilities to close those gaps.\r\nHelp teams judge generated output, understand why results vary, and get closer to what they want.\r\nIntegrate new image and video generation models into a multi-stage production pipeline.\r\nOperate and debug GPU workloads to keep generation reliable and cost-effective.\r\nMinimum QualificationsBachelor's degree in Computer Science, Computer Engineering, or a related field, or 3 years of equivalent work experience.\r\n3+ years of experience building and operating production software in Python.\r\nExperience debugging distributed systems or data pipelines in production, using logs, metrics, and task state to find root causes.\r\nExperience deploying machine learning models on GPU infrastructure, including dependency management and GPU memory sizing.\r\nExperience designing input validation and configuration contracts for systems where late failures are costly.\r\nDemonstrated ability to explain machine learning concepts and tradeoffs to non-technical partners such as designers or product managers.\r\nProven, hands-on use of agentic AI coding tools in day-to-day software development, including judging where they are effective and where their output needs human verification.\r\nPreferred QualificationsExperience working directly with partner teams or internal customers to define and ship features.\r\nExperience measuring the domain gap between synthetic and real data, including visual statistics and non-visual properties such as metadata and label distributions.\r\nExperience with generative image, video, or large language model APIs, including structured output.\r\nFamiliarity with image and video file formats and metadata standards.\r\nExperience with batch compute platforms or job schedulers.\r\nAt 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 $150,400 and $225,300, and your base pay will depend on your skills, qualifications, experience, and location.\r\nApple 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\r\nNote: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.\r\nApple 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\r\nAt 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\r\nApple accepts applications to this posting on an ongoing basis.#J-18808-Ljbffr","company":"JobLeads","rawCompany":"jobleadsus","city":"Millbrae","state":"CA","isRemote":false,"isActive":false,"createdAt":"2026-10-05T01:27:17.332Z","occupations":[{"code":"15-1252.00","title":"Software Developers","slug":"software-developers"},{"code":"15-1299.08","title":"Computer Systems Engineers/Architects","slug":"computer-systems-engineers-architects"},{"code":"15-2051.00","title":"Data Scientists","slug":"data-scientists"}],"industries":[{"code":"513210","title":"Software Publishers","slug":"software-publishers"},{"code":"541511","title":"Custom Computer Programming Services","slug":"custom-computer-programming-services"},{"code":"541512","title":"Computer Systems Design Services","slug":"computer-systems-design-services"}],"jobPosting":{"@context":"https://schema.org","@type":"JobPosting","title":"Software Engineer - Generative Data Platform, Evaluation","description":"Software Engineer - Generative Data Platform, EvaluationSan Francisco, California, United States Software and Services\r\nApple's machine learning features are only as good as the data behind them, and our team builds the platform that lets teams create data that fills the gaps real-world collection can't, provides privacy-preserving ways to train and evaluate our models safely, and helps us ensure our products have seen diverse inputs to generalize properly across the many parts of the world where we operate.In the AI & Machine Learning (AIML) organization, our team builds the self-service tools and platform that turn ideas, text, and images into large-scale generated datasets. We don't produce the datasets ourselves: ML engineers, data scientists, designers, feature teams, ML data operations teams, and Safety and Responsible AI teams across Apple use our platform to generate their own. That data is only valuable if it matches the real world closely enough to train on and to evaluate against, proving our models and features meet Apple's quality bar before they reach customers. As a software engineer on the platform, you'll sit between that technology and the people who depend on it: understanding what they want to create, building the features that make it possible, and helping them get the most from generative AI. It's a hands-on engineering role for someone who enjoys the people side as much as the code.\r\nDescriptionYou'll spend your days moving between engineering and partnership. Synthetic data here does far more than fill gaps: it lets teams build privacy-preserving digital humans, represent locales and domains that real-world collection underserves, and experiment in days instead of waiting on slow, costly data collection. It also gives Safety and Responsible AI red teams the data they need to stress-test models against misuse and edge cases. One day you might be integrating a new image or video generation model and tuning how it runs on GPUs; the next, you might be helping a design team get their first dataset running on the platform, or working with a feature team on model ablations that measure what synthetic data adds to training and evaluation.You'll help teams understand where synthetic data differs from the real data their models see, whether that's how images look or subtler differences in metadata, distributions, and labels, and then build what closes those gaps. Your core partners are ML engineers and data scientists, but you'll also work with designers, artists, and others who are newer to machine learning, and help make these systems understandable and approachable for them. You'll own features end to end, from shaping the request with partner teams to validating the result on production infrastructure.Our team builds with AI coding agents every day, and you'll help shape how we use them well. You don't need a research background in generative models; you'll learn the models on the job. What matters most is strong engineering judgment and the ability to bring people along.\r\nResponsibilitiesPartner with ML engineers, data scientists, and designers to turn their needs into platform features.\r\nSupport teams as they build their own datasets on the platform, and help design model ablations that measure how synthetic data affects training and evaluation.\r\nExplain how ML, vision, and generative models behave to people new to them, including cost, quality, speed, and feasibility.\r\nAssess the domain gap between synthetic and real data, covering visual properties and non-visual ones such as metadata, value distributions, and labels.\r\nWork with feature teams to find where synthetic data falls short for their use case, and build platform capabilities to close those gaps.\r\nHelp teams judge generated output, understand why results vary, and get closer to what they want.\r\nIntegrate new image and video generation models into a multi-stage production pipeline.\r\nOperate and debug GPU workloads to keep generation reliable and cost-effective.\r\nMinimum QualificationsBachelor's degree in Computer Science, Computer Engineering, or a related field, or 3 years of equivalent work experience.\r\n3+ years of experience building and operating production software in Python.\r\nExperience debugging distributed systems or data pipelines in production, using logs, metrics, and task state to find root causes.\r\nExperience deploying machine learning models on GPU infrastructure, including dependency management and GPU memory sizing.\r\nExperience designing input validation and configuration contracts for systems where late failures are costly.\r\nDemonstrated ability to explain machine learning concepts and tradeoffs to non-technical partners such as designers or product managers.\r\nProven, hands-on use of agentic AI coding tools in day-to-day software development, including judging where they are effective and where their output needs human verification.\r\nPreferred QualificationsExperience working directly with partner teams or internal customers to define and ship features.\r\nExperience measuring the domain gap between synthetic and real data, including visual statistics and non-visual properties such as metadata and label distributions.\r\nExperience with generative image, video, or large language model APIs, including structured output.\r\nFamiliarity with image and video file formats and metadata standards.\r\nExperience with batch compute platforms or job schedulers.\r\nAt 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 $150,400 and $225,300, and your base pay will depend on your skills, qualifications, experience, and location.\r\nApple 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\r\nNote: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.\r\nApple 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\r\nAt 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\r\nApple accepts applications to this posting on an ongoing basis.#J-18808-Ljbffr","datePosted":"2026-10-05T01:27:17.332Z","dateModified":"2026-10-05T01:27:17.332Z","hiringOrganization":{"@type":"Organization","name":"JobLeads","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Millbrae","addressRegion":"CA","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"1148ec15ba507bfc6464ec2b"},"url":"https://jobsearcher.com/jobs/1148ec15ba507bfc6464ec2b"}}