Full Stack Software Engineer - Camera & Photos Tools & AI Team
Apple
7 days ago
On-site
Cupertino, California, United States
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 \u0026 Photos Tools \u0026 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
Design and build AI-powered features within internal tools, including LLM integrations,\\nagentic workflows, and vision model pipelines for automated image quality analysis.\\nEvaluate, integrate, and maintain AI/ML models in production: monitoring for quality\\nregression, managing model versions, and balancing cost, latency, and accuracy tradeoffs\\nacross the service lifecycle.\\nDevelop prompt engineering strategies and retrieval-augmented systems (RAG) that make\\ninternal image and metadata corpora accessible and actionable to partner teams.\\nLeverage AI coding assistants and productivity tooling to accelerate development cycles\\nand raise overall team velocity.\\nPlan, design, implement, and own Swift applications used by imaging engineers and quality\\nteams.\\nBuild and evolve React/JavaScript web frontends that surface data, tooling, and workflows\\nto a broad internal audience.\\nDevelop and maintain Python REST API backends, including endpoints that kick off and\\nmonitor long-running asynchronous jobs.\\nPartner with engineers, scientists, and quality leads across Camera, Photos, and Image\\nQuality to understand their workflows and translate them into reliable tools.\\nDrive the reliability, performance, and observability of services that other teams depend on\\ndaily.\\nContribute to technical design discussions, code review, and cross-team planning; raise\\nthe bar for the engineers around you.
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\\nof contributing meaningfully in both client and server code.\\nStrong understanding of REST API design and experience building production REST\\nservices.\\nExperience building web frontends with React or a similar framework.\\nDemonstrated experience integrating AI/ML models (LLMs, vision models, or similar) into\\nproduction software systems, not just as a user but as a builder responsible for reliability\\nand maintainability.\\nWorking knowledge of asynchronous job execution patterns (background workers, task\\nqueues, or similar) for long-running computations.\\nSolid understanding of software engineering fundamentals: data modeling, API design,\\ntesting, debugging, and code review.\\nStrong written and verbal communication skills, with a demonstrated ability to work\\neffectively with partners outside of engineering.
Experience building production features with LLM APIs (e.g., OpenAI, Anthropic, or on-\\ndevice models), including prompt design, context window management, output validation,\\nand graceful degradation.\\nFamiliarity with multimodal or computer vision models applied to image analysis, quality\\nassessment, or visual data retrieval, with an understanding of where these models succeed\\nand fail in practice.\\nExperience with vector databases or semantic search (e.g., pgvector, Pinecone, Weaviate)\\nfor unstructured or high-dimensional data retrieval pipelines.\\nUnderstanding of MLOps principles: model deployment pipelines, versioning strategies,\\nevaluation frameworks, A/B testing for AI features, and production monitoring for model\\nquality and cost.\\nAwareness of bias and fairness considerations in AI systems, particularly in visual domains,\\nincluding diverse evaluation datasets, inclusive quality benchmarks, and responsible\\ndeployment practices.\\nExperience developing native macOS or iOS applications in Swift, including familiarity with\\nXcode.\\nExperience designing and operating distributed systems, including awareness of the\\ntradeoffs involved in consistency, coordination, and failure handling.\\nFamiliarity with Solr (or other search platforms such as Elasticsearch) for indexing and\\nquerying 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,\\nand presenting technical work to non-engineering partners.\\nComfortable and adaptable in a fast-paced environment with shifting priorities and multiple\\nstakeholders.
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
Design and build AI-powered features within internal tools, including LLM integrations,\\nagentic workflows, and vision model pipelines for automated image quality analysis.\\nEvaluate, integrate, and maintain AI/ML models in production: monitoring for quality\\nregression, managing model versions, and balancing cost, latency, and accuracy tradeoffs\\nacross the service lifecycle.\\nDevelop prompt engineering strategies and retrieval-augmented systems (RAG) that make\\ninternal image and metadata corpora accessible and actionable to partner teams.\\nLeverage AI coding assistants and productivity tooling to accelerate development cycles\\nand raise overall team velocity.\\nPlan, design, implement, and own Swift applications used by imaging engineers and quality\\nteams.\\nBuild and evolve React/JavaScript web frontends that surface data, tooling, and workflows\\nto a broad internal audience.\\nDevelop and maintain Python REST API backends, including endpoints that kick off and\\nmonitor long-running asynchronous jobs.\\nPartner with engineers, scientists, and quality leads across Camera, Photos, and Image\\nQuality to understand their workflows and translate them into reliable tools.\\nDrive the reliability, performance, and observability of services that other teams depend on\\ndaily.\\nContribute to technical design discussions, code review, and cross-team planning; raise\\nthe bar for the engineers around you.
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\\nof contributing meaningfully in both client and server code.\\nStrong understanding of REST API design and experience building production REST\\nservices.\\nExperience building web frontends with React or a similar framework.\\nDemonstrated experience integrating AI/ML models (LLMs, vision models, or similar) into\\nproduction software systems, not just as a user but as a builder responsible for reliability\\nand maintainability.\\nWorking knowledge of asynchronous job execution patterns (background workers, task\\nqueues, or similar) for long-running computations.\\nSolid understanding of software engineering fundamentals: data modeling, API design,\\ntesting, debugging, and code review.\\nStrong written and verbal communication skills, with a demonstrated ability to work\\neffectively with partners outside of engineering.
Experience building production features with LLM APIs (e.g., OpenAI, Anthropic, or on-\\ndevice models), including prompt design, context window management, output validation,\\nand graceful degradation.\\nFamiliarity with multimodal or computer vision models applied to image analysis, quality\\nassessment, or visual data retrieval, with an understanding of where these models succeed\\nand fail in practice.\\nExperience with vector databases or semantic search (e.g., pgvector, Pinecone, Weaviate)\\nfor unstructured or high-dimensional data retrieval pipelines.\\nUnderstanding of MLOps principles: model deployment pipelines, versioning strategies,\\nevaluation frameworks, A/B testing for AI features, and production monitoring for model\\nquality and cost.\\nAwareness of bias and fairness considerations in AI systems, particularly in visual domains,\\nincluding diverse evaluation datasets, inclusive quality benchmarks, and responsible\\ndeployment practices.\\nExperience developing native macOS or iOS applications in Swift, including familiarity with\\nXcode.\\nExperience designing and operating distributed systems, including awareness of the\\ntradeoffs involved in consistency, coordination, and failure handling.\\nFamiliarity with Solr (or other search platforms such as Elasticsearch) for indexing and\\nquerying 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,\\nand presenting technical work to non-engineering partners.\\nComfortable and adaptable in a fast-paced environment with shifting priorities and multiple\\nstakeholders.