{"id":2774744,"url":"https://alion.io/job/apple-data-scientist-intelligent-experiences-mlo","title":"Data Scientist - Intelligent Experiences, MLO","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":"B","score":81,"open_postings":969,"ghost_share":0,"stale_share":0.765,"repost_share":0,"time_to_fill_p50_days":49,"computed_at":"2026-10-19T05:45:15Z"}},"role":"Data Science","role_family":"Data Science","seniority":"senior","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":202000,"max_usd":386000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":1181},"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Agentic Workflows","optional":false},{"name":"AI Agents","optional":false},{"name":"Computer Vision","optional":false},{"name":"Diffusion Models","optional":false},{"name":"Fine-tuning","optional":false},{"name":"LLM","optional":false},{"name":"Machine Learning","optional":false},{"name":"Multimodal AI","optional":false},{"name":"NLP","optional":false},{"name":"Synthetic Data","optional":false},{"name":"AWS","optional":true},{"name":"DPO","optional":true},{"name":"GCP","optional":true},{"name":"Human-in-the-Loop","optional":true},{"name":"LoRA","optional":true},{"name":"PEFT","optional":true},{"name":"Python","optional":true},{"name":"QLoRA","optional":true},{"name":"RAG","optional":true},{"name":"Ray","optional":true},{"name":"RLHF","optional":true},{"name":"Spark","optional":true}],"status":"live","first_seen_at":"2026-10-17T05:45:22Z","employer_posted_date":"2026-10-17","last_verified_at":"2026-10-19T08:00:16Z","board_verified":true,"closed_at":null,"days_open":2,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":2},"description":"Do you believe machine learning and AI can change the world? We do. We're the ML Data team within Apple's Intelligent System Experience (ISE) group, and we build the high-quality, high-scale datasets that train the ML features across many Apple products - iPhone, iPad, Mac, Apple Watch, and AirPods. Our work sits behind some of the most visible and personal experiences Apple ships: the wallpaper on your Lock Screen, personalized stickers in iMessage, on-device Genmoji and other Apple Intelligence generative models, and models that recognize faces and build memories of the people you love in Photos.\nWe're looking for a data scientist who's passionate about ML data and excited to shape the training data behind Apple's next generation of multi-modal features. The ideal candidate thrives in a fast-paced environment, brings rigorous scientific reasoning and owns problems end-to-end.\nJoin us and you’ll shape shipping products from your first week, working with petabytes of multi-modal data.\nDescription\nYou will design and operate the end-to-end data lifecycle that supports training, fine-tuning, and evaluation of large language models and diffusion models. Day to day, that means building distributed pipelines that clean, deduplicate, and enrich massive multi-modal datasets; standing up synthetic data generation pipelines with LLM-based generators, validators, and judges; and engineering agentic workflows - multi-step, tool-using LLM systems - that scale human judgment across far more data than a human team could review directly.\nMinimum Qualifications\nBachelor's or Master's degree in Computer Science, Machine Learning, Data Science, or a related engineering field\n5+ years of hands-on experience applying NLP, computer vision, or multimodal machine learning to production systems, including experience with large-scale data pipelines\nPreferred Qualifications\nExperience prompting, fine-tuning, and evaluating LLMs or vision-language/diffusion models for specific downstream tasks\nExperience with parameter-efficient fine-tuning (LoRA/QLoRA), preference optimization (RLHF, DPO), RAG and retrieval-based data curation\nExperience designing, evaluating and productionizing data science algorithms used for data curation, data filtering, deduplication and data down-selection.\nExperience designing controlled experiments or ablation studies to understand effect of data on model quality\nExperience building agentic or multi-agent, tool-using LLM systems and human-in-the-loop workflows, calibrating judges against human labels, and mitigating failure modes\nStrong software engineering skills, with 5+ years in Python, workflow orchestration (Airflow), cloud platforms (AWS, GCP), distributed data processing frameworks (Spark, Ray, or similar) at large scale\nPublication record or open-source contributions in NLP, computer vision, or generative AI is a plus\nFamiliarity with privacy-preserving data techniques (e.g., differential privacy, on-device data constraints) is a 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