Build and maintain product features for internal developer platforms and AI tooling using React and TypeScript Integrate UI surfaces with backend APIs and ML services to create end-to-end, user-facing workflows Contribute to backend services supporting ML workloads, including data ingestion, model evaluation, and inference endpoints Write well-tested, production-ready code with attention to reliability, performance, and developer experience Collaborate with senior engineers, product managers, and partner teams to understand requirements and deliver solutions Participate in design reviews, code reviews, and on-call rotations as you grow into the role Contribute to improving observability, monitoring dashboards, and tooling for ML systems Document your work and contribute to team knowledge sharing1 or more years of industry experience building production software Proficiency in Python and JavaScript/TypeScript Familiarity with REST APIs and backend service integration Basic understanding of ML concepts, model inference, evaluation, or data pipelines Contributions to open-source projects or experience building internal developer tooling Strong communication skills and ability to work collaboratively in a team environment Curiosity, a growth mindset, and willingness to work across the stack BS/MS in Computer Science, Software Engineering, or a related field with applicable internship or project experienceExperience building product experiences or web applications with React or a comparable modern framework Experience with cloud environments (AWS, GCP, or Azure), Docker, or CI/CD pipelines Familiarity with ML frameworks such as PyTorch, Hugging Face, or LangChain Exposure to LLM application development, RAG, prompt engineering, evaluation pipelines, or agentic workflows Experience with data infrastructure tools such as Spark, Kafka, or SQL-based analytics systems Ability to work independently on scoped features with minimal supervision. We are looking for a Software Engineer who is eager to build the tools, interfaces, and workflows that ML developers and researchers use every day from intuitive front-end experiences to backend services and ML integrations at Apple scale.