{"schemaVersion":"jobsearcher.job.v1","id":"da8d35f8153fa5187fcbff43","url":"https://jobsearcher.com/jobs/da8d35f8153fa5187fcbff43","canonicalUrl":"https://jobsearcher.com/jobs/da8d35f8153fa5187fcbff43","title":"Machine Learning Evaluation Engineer","description":"We are looking for a highly motivated Machine Learning Evaluation Engineer to join our team and help define and drive the evaluation of advanced machine learning and computer vision technologies. You will work closely with algorithm, data, and engineering teams to build scalable evaluation methodologies, uncover model weaknesses, and turn complex data into actionable insights.\n\nYou will play a key role in ensuring that our ML systems deliver high-quality, robust experiences across diverse real-world scenarios. The ideal candidate combines strong fundamentals in classical machine learning and computer vision with hands-on experience in metrics design, data analysis, failure analysis, visualization, and evaluation infrastructure. You should also be comfortable leveraging modern AI-assisted tools and workflows to improve engineering efficiency and accelerate analysis.\n\nDescription\n\nIn this role, you will define and drive the evaluation strategy for computer vision and machine learning algorithms used in complex product experiences. You will work closely with algorithm engineers to understand system behavior, identify the most meaningful quality signals, and develop evaluation frameworks that reflect real-world performance.\n\nYou will design metrics and evaluation methodologies that go beyond aggregate accuracy and help the team understand performance across important data slices and scenarios. You will analyze large-scale datasets to identify gaps in data quality and coverage and develop strategies to improve the representativeness of training and evaluation data.\n\nA significant part of this role will involve failure analysis. You will investigate model failures, identify recurring patterns, develop failure taxonomies, and determine whether issues are driven by data, labeling, algorithm limitations, environmental conditions, or other system-level factors. You will build tools and visualizations that enable engineers to efficiently explore failures and understand the underlying root causes.\n\nYou will also develop scalable and automated workflows for evaluation, analysis, and reporting. You will be expected to leverage modern AI-assisted tools where appropriate to accelerate data analysis, visualization development, coding, and workflow automation while maintaining technical rigor and reproducibility.\n\nAs a member of the team, you will help shape evaluation best practices, influence algorithm and data decisions, and drive improvements across the ML development lifecycle. You should be comfortable navigating ambiguity, independently identifying opportunities for improvement, and partnering with cross-functional teams to deliver high-quality ML systems.\n\nPreferred Qualifications\n\nMS in Computer Science, Computer Engineering, Electrical Engineering, Statistics, Applied Mathematics, or a related technical field (Advanced degree is a plus)\n\nExperience evaluating computer vision algorithms such as object detection, classification, tracking, segmentation, pose estimation, or hand tracking.\n\nExperience with large-scale ML datasets and data pipelines.\n\nExperience developing internal tools or platforms for ML evaluation and analysis.\n\nExperience with deep learning frameworks and modern ML systems.\n\nExperience with synthetic data, data augmentation, or automated data generation.\n\nFamiliarity with model monitoring, regression detection, and production ML quality systems.\n\nExperience applying generative AI or AI-assisted workflows to engineering and analytical tasks.\n\nExperience mentoring engineers or providing technical leadership for complex evaluation initiatives.\n\nExcellent communication skills and the ability to collaborate effectively across algorithm, engineering, data, and product teams.\n\nMinimum Qualifications\n\nBS and a minimum of 3 years relevant industry experience\n\n3+ years of relevant industry experience in machine learning, computer vision, algorithm evaluation, data science, or a related field.\n\nStrong background in machine learning and computer vision, including classical ML and statistical modeling techniques.\n\nProven experience designing and implementing evaluation methodologies and quality metrics for ML algorithms.\n\nStrong expertise in failure analysis and root-cause analysis, with the ability to identify systematic model weaknesses and translate findings into actionable recommendations.\n\nExperience analyzing data quality, diversity, representativeness, and coverage gaps across large and complex datasets.\n\nStrong programming skills in Python with experience in data processing, analysis, and visualization.\n\nExperience building automated and scalable evaluation pipelines and tooling.\n\nAbility to develop clear and insightful visualizations and dashboards that communicate model performance, regressions, and failure patterns.\n\nStrong understanding of statistical analysis, experimentation, and performance measurement.\n\nAbility to independently drive ambiguous technical problems from problem definition through analysis and recommendations.\n\nExperience using AI-powered development and analysis tools to improve productivity, accelerate data exploration, automate repetitive workflows, and improve engineering efficiency.\n\nPay & Benefits\n\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 $277,600, and your base pay will depend on your skills, qualifications, experience, and location.\n\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\n\nNote: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.","company":"Apple","rawCompany":"apple","city":"Sunnyvale","state":"CA","isRemote":false,"isActive":true,"createdAt":"2026-09-01T10:39:45.823Z","occupations":[{"code":"17-2112.02","title":"Validation Engineers","slug":"validation-engineers"},{"code":"15-2051.00","title":"Data Scientists","slug":"data-scientists"},{"code":"15-1299.08","title":"Computer Systems Engineers/Architects","slug":"computer-systems-engineers-architects"}],"industries":[{"code":"541690","title":"Other Scientific and Technical Consulting Services","slug":"other-scientific-and-technical-consulting-services"},{"code":"541512","title":"Computer Systems Design Services","slug":"computer-systems-design-services"},{"code":"541330","title":"Engineering Services","slug":"engineering-services"}],"jobPosting":{"@context":"https://schema.org","@type":"JobPosting","title":"Machine Learning Evaluation Engineer","description":"We are looking for a highly motivated Machine Learning Evaluation Engineer to join our team and help define and drive the evaluation of advanced machine learning and computer vision technologies. You will work closely with algorithm, data, and engineering teams to build scalable evaluation methodologies, uncover model weaknesses, and turn complex data into actionable insights.\n\nYou will play a key role in ensuring that our ML systems deliver high-quality, robust experiences across diverse real-world scenarios. The ideal candidate combines strong fundamentals in classical machine learning and computer vision with hands-on experience in metrics design, data analysis, failure analysis, visualization, and evaluation infrastructure. You should also be comfortable leveraging modern AI-assisted tools and workflows to improve engineering efficiency and accelerate analysis.\n\nDescription\n\nIn this role, you will define and drive the evaluation strategy for computer vision and machine learning algorithms used in complex product experiences. You will work closely with algorithm engineers to understand system behavior, identify the most meaningful quality signals, and develop evaluation frameworks that reflect real-world performance.\n\nYou will design metrics and evaluation methodologies that go beyond aggregate accuracy and help the team understand performance across important data slices and scenarios. You will analyze large-scale datasets to identify gaps in data quality and coverage and develop strategies to improve the representativeness of training and evaluation data.\n\nA significant part of this role will involve failure analysis. You will investigate model failures, identify recurring patterns, develop failure taxonomies, and determine whether issues are driven by data, labeling, algorithm limitations, environmental conditions, or other system-level factors. You will build tools and visualizations that enable engineers to efficiently explore failures and understand the underlying root causes.\n\nYou will also develop scalable and automated workflows for evaluation, analysis, and reporting. You will be expected to leverage modern AI-assisted tools where appropriate to accelerate data analysis, visualization development, coding, and workflow automation while maintaining technical rigor and reproducibility.\n\nAs a member of the team, you will help shape evaluation best practices, influence algorithm and data decisions, and drive improvements across the ML development lifecycle. You should be comfortable navigating ambiguity, independently identifying opportunities for improvement, and partnering with cross-functional teams to deliver high-quality ML systems.\n\nPreferred Qualifications\n\nMS in Computer Science, Computer Engineering, Electrical Engineering, Statistics, Applied Mathematics, or a related technical field (Advanced degree is a plus)\n\nExperience evaluating computer vision algorithms such as object detection, classification, tracking, segmentation, pose estimation, or hand tracking.\n\nExperience with large-scale ML datasets and data pipelines.\n\nExperience developing internal tools or platforms for ML evaluation and analysis.\n\nExperience with deep learning frameworks and modern ML systems.\n\nExperience with synthetic data, data augmentation, or automated data generation.\n\nFamiliarity with model monitoring, regression detection, and production ML quality systems.\n\nExperience applying generative AI or AI-assisted workflows to engineering and analytical tasks.\n\nExperience mentoring engineers or providing technical leadership for complex evaluation initiatives.\n\nExcellent communication skills and the ability to collaborate effectively across algorithm, engineering, data, and product teams.\n\nMinimum Qualifications\n\nBS and a minimum of 3 years relevant industry experience\n\n3+ years of relevant industry experience in machine learning, computer vision, algorithm evaluation, data science, or a related field.\n\nStrong background in machine learning and computer vision, including classical ML and statistical modeling techniques.\n\nProven experience designing and implementing evaluation methodologies and quality metrics for ML algorithms.\n\nStrong expertise in failure analysis and root-cause analysis, with the ability to identify systematic model weaknesses and translate findings into actionable recommendations.\n\nExperience analyzing data quality, diversity, representativeness, and coverage gaps across large and complex datasets.\n\nStrong programming skills in Python with experience in data processing, analysis, and visualization.\n\nExperience building automated and scalable evaluation pipelines and tooling.\n\nAbility to develop clear and insightful visualizations and dashboards that communicate model performance, regressions, and failure patterns.\n\nStrong understanding of statistical analysis, experimentation, and performance measurement.\n\nAbility to independently drive ambiguous technical problems from problem definition through analysis and recommendations.\n\nExperience using AI-powered development and analysis tools to improve productivity, accelerate data exploration, automate repetitive workflows, and improve engineering efficiency.\n\nPay & Benefits\n\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 $277,600, and your base pay will depend on your skills, qualifications, experience, and location.\n\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\n\nNote: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.","datePosted":"2026-09-01T10:39:45.823Z","dateModified":"2026-09-01T10:39:45.823Z","hiringOrganization":{"@type":"Organization","name":"Apple","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Sunnyvale","addressRegion":"CA","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"da8d35f8153fa5187fcbff43"},"url":"https://jobsearcher.com/jobs/da8d35f8153fa5187fcbff43"}}