{"id":2991143,"url":"https://alion.io/job/apple-applied-machine-learning-engineer-apple-intelligence","title":"Applied Machine Learning Engineer, Apple Intelligence","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":90,"open_postings":844,"ghost_share":0,"stale_share":0.188,"repost_share":0.002,"time_to_fill_p50_days":92,"computed_at":"2026-11-04T06:34:25Z"}},"role":"AI/ML","role_family":"AI/ML","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":["Bengaluru, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":38000,"max_usd":78000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":41},"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"C++","optional":false},{"name":"Claude","optional":false},{"name":"Cursor","optional":false},{"name":"Multi-Agent Systems","optional":false},{"name":"NLP","optional":false},{"name":"Objective-C","optional":false},{"name":"OpenAI Codex","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false},{"name":"Tokenization","optional":false},{"name":"LLM","optional":true},{"name":"PyTorch","optional":true},{"name":"TensorFlow","optional":true},{"name":"TensorFlow C++","optional":true}],"status":"live","first_seen_at":"2026-09-07T05:49:20Z","employer_posted_date":"2026-10-21","last_verified_at":"2026-11-04T15:13:36Z","board_verified":true,"closed_at":null,"days_open":58,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":58},"description":"Apple is where individual imaginations gather together, committing to the values that lead to great work. Every new product we build or service we create, we deliver is the result of us making each other’s ideas stronger. That happens because every one of us shares a belief that we can make something wonderful and share it with the world, changing lives for the better. It’s the diversity of our people and their thinking that inspires the innovation that runs through everything we do. When we bring everybody in, we can do the best work of our lives. Here, you’ll do more than join something - you’ll add something.\nDescription\nAs part of Apple Intelligence, you'll bring impact to billions of users through your applied ML skills, engineering rigor, and programming expertise. You will work alongside a dedicated team of ML and software engineers, applying and integrating generative modeling techniques into production systems.\nOur team focuses on generative technologies for key international markets, and you'll help own components across the pipeline, from data preprocessing to evaluation and deployment, ensuring our systems are culturally and linguistically adaptable across a range of local experiences.\nYou are passionate about coding and software development lifecycle methodologies, with a strong focus on debugging and performance. The specific platforms, frameworks, and components will change over time, so we're looking for someone who can transition smoothly across them and bring strong evaluation and systems engineering fundamentals to whatever the team needs next.\nIf you're an engineer with strong applied ML who enjoys building generative AI systems that reach real users at scale, this is a great opportunity to make a meaningful impact.\nMinimum Qualifications\n5+ years of hands-on ML experience building harnesses and integrating models into production workflows, using Python plus one or more of C/C++/Objective-C/Swift, on a strong software engineering foundation (OS fundamentals, OOPS).\nProven hands-on IC coder - this role is technical, not architectural - who ships clean, well-tested, maintainable code\nStrong practical use of generative-AI coding tools, specifically Claude/Cursor/Codex\nStrong debugging, systems-thinking, and problem-solving skills, demonstrated through code reviews, architectural discussions, and production troubleshooting.\nApplied experience across NLP (tokenization, language modeling, decoding, classification), modern agentic and multi-agent systems, and RAG architectures.\nPreferred Qualifications\nExperience staging, provisioning, or controlling test or evaluation environments to produce repeatable, deterministic conditions\nExperience evaluating ML, LLM or agent-based systems, including familiarity with metrics, scoring methodology, or trajectory and outcome analysis\nExperience building, maintaining, or operating production-grade AI agents at scale - 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