{"id":2758255,"url":"https://alion.io/job/apple-engineering-leader-ai-safety-engineering-evaluation-apple-services-engineering","title":"Engineering Leader, AI Safety Engineering & Evaluation, Apple Services Engineering","company":{"id":12,"name":"Apple","domain":"apple.com","url":"https://alion.io/company/apple","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Apple Jobs","truth_index":{"grade":"A","score":91,"open_postings":911,"ghost_share":0.001,"stale_share":0.151,"repost_share":0.003,"time_to_fill_p50_days":99,"computed_at":"2026-10-27T05:46:45Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"lead","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Cupertino, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":254000,"max_usd":527000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":782},"experience_years_min":12,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Machine Learning","optional":false},{"name":"Python","optional":false},{"name":"AI Agents","optional":true},{"name":"LLM","optional":true},{"name":"Red Teaming","optional":true},{"name":"Synthetic Data","optional":true}],"status":"live","first_seen_at":"2026-10-16T23:57:57Z","employer_posted_date":"2026-10-17","last_verified_at":"2026-10-27T03:45:41Z","board_verified":true,"closed_at":null,"days_open":10,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":10},"description":"Apple Services Engineering (ASE) powers AI and machine learning experiences across the App Store, Apple Music, Apple TV, and more. We build intelligent, deeply personal experiences designed to serve users around the world. Ensuring these experiences are safe, trustworthy, and representative of the diverse communities we serve is fundamental to how we develop and deploy AI.\nWe are seeking an experienced engineering leader to lead AI Safety Engineering & Evaluation within the Human-Centered AI organization. This role combines software engineering, machine learning, evaluation science, and Responsible AI to develop scalable capabilities for identifying, measuring, and mitigating risks associated with AI-powered experiences.\nYou will lead an emerging, multidisciplinary organization of engineering managers, engineers, and applied scientists, building the technical expertise, engineering practices, and organizational capabilities needed to scale AI safety evaluation. This is an opportunity to shape a growing function, developing its technical foundations while transforming manual safety assessments into automated, scientifically rigorous processes.\nThe ideal candidate brings strong engineering leadership, practical expertise in machine learning and modern AI systems, and demonstrated success building technical organizations and translating complex challenges into measurable engineering outcomes.\nDescription\nAs the Engineering Leader for AI Safety Engineering & Evaluation, you will lead the development and operationalization of technical capabilities to systematically assess AI model behavior, identify potential harms, and measure the effectiveness of safety mitigations.\nYour organization will advance safety evaluation methodologies, model-based assessment, adversarial testing, automated risk identification, and failure analysis. In partnership with Evaluation Systems & Research (ESR), which provides shared evaluation infrastructure and services, you will integrate safety-specific models, assessment workflows, and measurement capabilities into scalable evaluation systems.\nYou will establish the technical direction, organizational structure, and engineering practices needed for a growing team to operate effectively. This requires a leader who can engage deeply in technical decisions, develop engineering managers and senior contributors, and progressively build the organization's ability to deliver complex technical solutions.\nYou will work closely with machine learning engineering, research, product, privacy, legal, and safety policy teams to translate safety requirements into measurable technical standards and actionable insights that inform AI development and deployment decisions.\nMinimum Qualifications\n12+ years of experience in software engineering, machine learning engineering, applied AI, or related technical disciplines, including demonstrated experience delivering complex production-quality systems.\n8+ years of engineering or applied machine learning management experience, including at least 3 years managing engineering managers or leading multiple technical teams through established managers.\nDemonstrated experience building or transforming engineering organizations, including developing technical talent, establishing engineering practices, and scaling teams through periods of organizational or technical growth.\nStrong software engineering foundation, including experience guiding architecture, implementation, and operationalization of complex software or AI/ML solutions.\nPractical expertise in machine learning and modern AI architectures, including model development, inference, and evaluation methodologies.\nStrong technical foundation in Python and modern software development practices, with the ability to assess technical tradeoffs and guide engineering execution.\nDemonstrated ability to develop technical roadmaps, establish priorities, manage resources, and deliver measurable outcomes in ambiguous environments.\nExcellent communication and stakeholder management skills, with experience influencing senior technical and cross-functional leaders.\nBachelor's degree in Computer Science, Machine Learning, Engineering, or a related technical field, or equivalent practical experience.\nPreferred Qualifications\nExperience leading teams developing AI/ML evaluation systems, automated model assessment, or applied machine learning solutions.\nExperience with generative AI and large language models, including LLM-based evaluation, agentic systems, model orchestration, or adversarial testing.\nApplied experience with machine learning modeling, statistical analysis, experimental design, and quantitative evaluation methods.\nExperience developing automated model assessors, synthetic data generation, red teaming, or systematic failure analysis capabilities.\nFamiliarity with Responsible AI principles and technical approaches to fairness, bias, robustness, harmful content, and safety risk assessment.\nExperience integrating evaluation capabilities into existing engineering platforms, development workflows, or continuous measurement processes.\nExperience leading multidisciplinary engineering organizations through technical transformation, particularly involving automation or applied machine learning.\nAbility to translate emerging research techniques into reliable engineering implementations.\nAdvanced degree in Computer Science, Machine Learning, Artificial Intelligence, or a related technical discipline.","description_format":"text","description_chars":5483,"description_truncated":false,"requirements":{"experience_years_min":12,"management_years_min":3,"team_size_min":null,"manages_managers":true,"education":{"level":"bachelor","optional":false},"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Operating Systems","Laptops","Smartwatches & Fitness Trackers","Tablets"],"lifecycle":[{"event":"open","at":"2026-10-17T02:14:05Z"}],"visa":[{"country":"US","licensed_sponsor":true,"evidence":"H-1B filings in 12 months: 6,350 · green card filings: 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