Full Stack Software Engineer - Camera & Photos Tools & AI Team

At Apple, new ideas have a way of becoming extraordinary products and experiences very\\nquickly. Bring your passion and dedication to your job and there's no telling what you could\\naccomplish.\\n\\nApple's Camera & Photos Tools & AI team is a tight-knit engineering team building the\\ninternal tools that power how the Camera, Photos, and Image Quality teams measure,\\nevaluate, and improve the imaging experience on Apple products. Our software sits at the\\ncenter of some of Apple's most demanding imaging workflows: it captures and catalogs\\nenormous volumes of images and videos, orchestrates long-running analyses that\\ncharacterize camera performance, and surfaces the results to the engineers and scientists\\nwho tune the hardware and software behind every photo our customers take.\\n\\nWe move quickly, care deeply about the craft, and thrive on turning ambiguous problems into\\nreliable, well-designed tools. As a member of this team, you will ship software across the full\\nstack, from native Swift applications and modern web frontends to Python service backends,\\nand you will partner with a wide range of engineering, science, and quality teams to\\nunderstand their workflows and build what they need.\\n\\nAs AI capabilities advance rapidly, our team is actively building AI-native tooling, from\\nintegrating multimodal and vision models into image quality workflows to designing LLM-\\npowered interfaces that let engineers query and interpret large datasets in natural language.\\nWe're looking for someone who doesn't just use AI as a productivity aid, but who thinks\\ncritically about where and how to embed it into reliable, maintainable engineering systems.\\n\\nIf you enjoy owning problems end-to-end, writing code that people rely on, and collaborating\\nwith partners across multiple disciplines, we would love to talk to you.

We are seeking a versatile and technically strong Software Engineer to help design, build,\nand own end-to-end development of the internal tooling that supports imaging engineering\nand quality workflows across Camera, Photos, and Image Quality. You will contribute to\nmultiple Swift applications, React-based web frontends, and Python REST API services, and\nleverage Apple infrastructure to run asynchronous compute jobs.\n\nThe ideal candidate is an experienced generalist who is comfortable moving between client,\nweb, and backend code; has a solid grasp of distributed-systems fundamentals; and writes\ncode with an eye toward maintainability, correctness, and long-term operability. You are\nequally at home designing a new service, debugging a tricky async job, polishing a UI\nworkflow, and sitting down with a partner team to understand what they actually need before\nwriting a line of code. You bring informed opinions about where AI genuinely improves a\nsystem, and where it adds unnecessary complexity, and you hold AI-powered features to the\nsame engineering standards as any other production code. Above all, you are a strong\ncommunicator who treats cross-functional collaboration as a core part of the job.\n

BS in Computer Science, Computer Engineering, or equivalent experience.\n4+ years of professional software engineering experience shipping production software.\nProficiency in at least two of: Swift, Python, and JavaScript/TypeScript, with a track record of contributing meaningfully in both client and server code.\nStrong understanding of REST API design and experience building production REST services.\nExperience building web frontends with React or a similar framework.\nDemonstrated experience integrating AI/ML models (LLMs, vision models, or similar) into production software systems, not just as a user but as a builder responsible for reliability and maintainability.\nWorking knowledge of asynchronous job execution patterns (background workers, task queues, or similar) for long-running computations.\nSolid understanding of software engineering fundamentals: data modeling, API design, testing, debugging, and code review.\nStrong written and verbal communication skills, with a demonstrated ability to work effectively with partners outside of engineering.

Experience building production features with LLM APIs (e.g., OpenAI, Anthropic, or on- device models), including prompt design, context window management, output validation, and graceful degradation.\nFamiliarity with multimodal or computer vision models applied to image analysis, quality assessment, or visual data retrieval, with an understanding of where these models succeed and fail in practice.\nExperience with vector databases or semantic search (e.g., pgvector, Pinecone, Weaviate) for unstructured or high-dimensional data retrieval pipelines.\nUnderstanding of MLOps principles: model deployment pipelines, versioning strategies, evaluation frameworks, A/B testing for AI features, and production monitoring for model quality and cost.\nAwareness of bias and fairness considerations in AI systems, particularly in visual domains, including diverse evaluation datasets, inclusive quality benchmarks, and responsible deployment practices.\nExperience developing native macOS or iOS applications in Swift, including familiarity with Xcode.\nExperience designing and operating distributed systems, including awareness of the tradeoffs involved in consistency, coordination, and failure handling.\nFamiliarity with Solr (or other search platforms such as Elasticsearch) for indexing and querying large datasets.\nFamiliarity with Redis, whether as a cache, message broker, or coordination primitive.\nComfort working with image data, metadata pipelines, or scientific/engineering workflows.\nExceptional cross-functional collaboration skills: stakeholder alignment, documentation, and presenting technical work to non-engineering partners.\nComfortable and adaptable in a fast-paced environment with shifting priorities and multiple stakeholders.