AIML - Sr Backend Engineer, Data and ML Innovation

Apple•Cupertino, CA

About The Position

The AI and Machine Learning team is looking for a 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.

Requirements

Bachelor's degree in Computer Science or related field.
10+ years of extensive backend development experience.
Solid foundational programming skills (algorithms, data structures, OOP, etc).
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.
Proficient in REST API.
Proficient in Redis.
Proficient in VectorDB or other large scale data storage systems.
In-depth knowledge of workflow orchestration systems like Airflow.
In-depth knowledge of distributed systems.
In-depth knowledge of cloud-native applications.
In-depth knowledge of containerization technologies like Docker and Kubernetes.

Nice To Haves

Knowledge of Data Engineering & ML domain & training lifecycle.
Experience in Data Engineering & ML domain & training lifecycle.
Experience with large-scale data processing.
Experience with distributed systems.
Experience with microservices.
Experience with various caching strategies.
Experience with performance optimization.
Excellent problem solving skills and ability 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.

Responsibilities

Building and maintaining the server-side logic.
Developing back-end components.
Connecting the application with third-party web services.
Supporting the front-end developers by integrating their work with the Python application.
Analyzing business requirements, identifying gaps, and translating requirements into technical designs.
Adhering to best practices of software development, such as agile development, code reviews, continuous integration, and automated testing.
Working closely with project managers, UI/UX designers, and other cross functional stakeholders to deliver high quality work on-time.
Building or integrating LLM-powered workflows, AI agents, and modern AI-assisted development practices.

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