Full Stack Software Engineer Camera & Photos Tools & AI Team

At Apple new ideas have a way of becoming extraordinary products and experiences verynquickly. Bring your passion and dedication to your job and theres no telling what you Camera u0026 Photos Tools u0026 AI team is a tight-knit engineering team building theninternal tools that power how the Camera Photos and Image Quality teams measurenevaluate and improve the imaging experience on Apple products. Our software sits at thencenter of some of Apples most demanding imaging workflows: it captures and catalogsnenormous volumes of images and videos orchestrates long-running analyses thatncharacterize camera performance and surfaces the results to the engineers and scientistsnwho tune the hardware and software behind every photo our customers move quickly care deeply about the craft and thrive on turning ambiguous problems intonreliable well-designed tools. As a member of this team you will ship software across the fullnstack from native Swift applications and modern web frontends to Python service backendsnand you will partner with a wide range of engineering science and quality teams tonunderstand their workflows and build what they AI capabilities advance rapidly our team is actively building AI-native tooling fromnintegrating multimodal and vision models into image quality workflows to designing LLM-npowered interfaces that let engineers query and interpret large datasets in natural looking for someone who doesnt just use AI as a productivity aid but who thinksncritically about where and how to embed it into reliable maintainable engineering you enjoy owning problems end-to-end writing code that people rely on and collaboratingnwith partners across multiple disciplines we would love to talk to you.

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

Design and build AI-powered features within internal tools including LLM integrations agentic workflows and vision model pipelines for automated image quality integrate and maintain AI/ML models in production: monitoring for quality regression managing model versions and balancing cost latency and accuracy tradeoffs across the service prompt engineering strategies and retrieval-augmented systems (RAG) that make internal image and metadata corpora accessible and actionable to partner AI coding assistants and productivity tooling to accelerate development cycles and raise overall team design implement and own Swift applications used by imaging engineers and quality and evolve React/JavaScript web frontends that surface data tooling and workflows to a broad internal and maintain Python REST API backends including endpoints that kick off and monitor long-running asynchronous with engineers scientists and quality leads across Camera Photos and Image Quality to understand their workflows and translate them into reliable the reliability performance and observability of services that other teams depend on to technical design discussions code review and cross-team planning; raise the bar for the engineers around you.

BS in Computer Science Computer Engineering or equivalent experience.n4 years of professional software engineering experience shipping production in at least two of: Swift Python and JavaScript/TypeScript with a track record of contributing meaningfully in both client and server understanding of REST API design and experience building production REST building web frontends with React or native macOS or iOS apps in 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 knowledge of asynchronous job execution patterns (background workers task queues or similar) for long-running understanding of software engineering fundamentals: data modeling API design testing debugging and code 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 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 with vector databases or semantic search (e.g. pgvector Pinecone Weaviate) for unstructured or high-dimensional data retrieval of MLOps principles: model deployment pipelines versioning strategies evaluation frameworks A/B testing for AI features and production monitoring for model quality and of bias and fairness considerations in AI systems particularly in visual domains including diverse evaluation datasets inclusive quality benchmarks and responsible deployment developing native macOS or iOS applications in Swift including familiarity with designing and operating distributed systems including awareness of the tradeoffs involved in consistency coordination and failure with Solr (or other search platforms such as Elasticsearch) for indexing and querying large with Redis whether as a cache message broker or coordination working with image data metadata pipelines or scientific/engineering cross-functional collaboration skills: stakeholder alignment documentation and presenting technical work to non-engineering and adaptable in a fast-paced environment with shifting priorities and multiple stakeholders.