AIML - Sr Backend Engineer, Data and ML Innovation

Apple
Apple

Software Engineering, Data Science

Cupertino, CA, USA

USD 184,700-324,800 / year + Equity

Posted on Jul 29, 2026
Are you excited to tackle some of the most ambitious technical challenges in Apple Intelligence? Be involved in collaborating closely with our machine learning researchers, engineers, and data scientists? Together, you will orchestrate groundbreaking research initiatives and develop transformative products designed to build a significant impact for billions of users worldwide! The AI and Machine Learning team is looking for Sr Backend Engineer to build world-class data solutions that are used by data scientists, ML engineers and researchers to power Apple Foundation Model lifecycle.
We are looking for a skilled Python Backend Engineer to join our development team. In this role, you will be responsible for building and maintaining the server-side logic. You will be tasked with developing back-end components, connecting the application with third-party web services, and supporting the front-end developers by integrating their work with the Python application. Our ideal candidate must have demonstrated expertise in Python. Knowledge of Data Engineering & ML domain & training lifecycle is an added plus. You are comfortable with analyzing business requirements, identifying gaps, and translating requirements into technical designs. You are proficient and adhere to the best practices of software development, such as agile development, code reviews, continuous integration, and automated testing. You have worked closely with project managers, UI/UX designers, and other cross functional stakeholders to deliver high quality work on-time. You are well-versed in GenAI tools and agentic development, with hands-on experience building or integrating LLM-powered workflows, AI agents, and modern AI-assisted development practices.
  • Design and develop scalable, high-performance backend systems and APIs using Python frameworks such as FastAPI, Django, or Flask.
  • Build and integrate LLM-powered workflows, AI agents, and agentic pipelines into production backend services.
  • Collaborate with front-end developers, product managers, and cross-functional stakeholders to translate business requirements into robust technical solutions.
  • Architect and maintain data pipelines, microservices, and cloud-native applications supporting ML training lifecycle and data engineering workflows.
  • Implement and enforce software development best practices including code reviews, automated testing, continuous integration, and agile methodologies.
  • Evaluate and integrate third-party web services, LLM APIs, and GenAI frameworks (e.g. LangChain, LlamaIndex, OpenAI) to extend platform capabilities.
  • Monitor, debug, and optimize backend systems for reliability, scalability, and performance in production environments.
  • Bachelor's degree in Computer Science or related field.
  • 10+ years of extensive backend development experience, with solid foundational programming skills (algorithms, data structures, OOP, etc) and experience designing, writing, reviewing, testing and delivering software for applications and systems at scale.
  • Expertise in architecting and developing backend systems using Python; extensive experience in FastAPI, Django, or Flask will be great.
  • Proficient in REST API, Redis, VectorDB or other large scale data storage systems.
  • In-depth knowledge of workflow orchestration systems like Airflow, distributed systems, cloud-native applications, and containerization technologies like Docker and Kubernetes.
  • Experience in Data Engineering & ML domain & training lifecycle.
  • Experience with large-scale data processing, distributed systems , microservices, various caching strategies, and performance optimization.
  • Excellent problem solving skills and be able to navigate through complex technical challenges and design decisions.
  • Experience with cloud platforms like AWS or GCP
  • Experience building and productionizing GenAI applications, including LLM integration, prompt engineering, RAG pipelines, and agentic workflows using frameworks such as LangChain or similar tools.
  • Master or Ph.D. in a related field.
  • Previous experience in a high-growth tech company or similar environment.