Software Engineer for GenAi Platforms, AiDP at Apple

Sunnyvale, California, United States -

Full Time

Start Date

Immediate

Expiry Date

02 May, 26

Salary

0.0

Posted On

01 Feb, 26

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Python, Java, Asynchronous Processing, Multithreading, Performance Optimization, Machine Learning, Cloud Services, Micro-services Architecture, React.js, Containerization, Kubernetes, CI/CD Pipelines, Automated Testing, Observability, Security Best Practices, Problem-solving

Industry

Computers and Electronics Manufacturing

Description

The people here at Apple don’t just build products — we craft the kind of wonder that’s revolutionized entire industries. It’s the diversity of those people and their ideas that supports the innovation that runs through everything we do, from amazing technology to industry-leading environmental efforts. Join Apple, and help us leave the world better than we found it. Imagine what you could do here! At Apple, new ideas have a way of becoming extraordinary products, services, and customer experiences very quickly. Bring passion and dedication to your job and there's no telling what you could accomplish. A passion for product ownership and track record will prove critical to success on our team. Be ready to make something extraordinary when here. Multifaceted, encouraging people and innovative, industry-defining technologies are the norm at Apple. Would you like to work in a fast-paced environment where your technical abilities will be challenged on a day to day basis? If so, Apple’s AI & Data Platform (AiDP) team is seeking a Software Engineer to build and scale best in class data and reporting apps presenting metrics & performance indicators with the least latency and outstanding user experience. We are looking for a team member that will be able to think creatively and should have a real passion for building highly scalable applications with end users in focus. You will engage directly with key business partners to understand the business strategies and solution needs. Your drive will be to lead functional and technical discussions with development teams, so you can design and own end-to-end applications. You will enjoy the benefits of working in a fast growing business where we are inspired to "Think Different" and where our efforts play a key role in the success of Apple's business. You will have an extraordinary opportunity to be a competent, expert, and results-oriented Software Engineer defining and building some of the best-in-class data platforms and products. DESCRIPTION In AiDP, we work on building intelligent systems to democratize AI across a wide range of solutions within Apple. You will drive the development and deployment of innovative AI models and systems directly impacting the capabilities and performance within Apple’s products and services. You will implement robust, scalable ML infrastructure, including data storage, processing, and model serving components, to support the seamless integration of AI/ML models into production environments. You will develop novel feature engineering, data augmentation, prompt engineering, and fine-tuning frameworks that achieve optimal performance on specific tasks and domains. We design and implement automated ML pipelines for data preprocessing, feature engineering, model training, hyper-parameter tuning, and model evaluation, enabling rapid experimentation and iteration. We also implement advanced model compression and optimization techniques to reduce the resource footprint of language models while preserving their performance. There are tremendous opportunities to deliver impactful influences to Apple. MINIMUM QUALIFICATIONS Coding: strong python and proficient in Java with deep knowledge of asynchronous processing, multithreading, and performance optimization Hands-on with public or private Cloud Services and serverless architectures Solid foundation in machine learning developing Agentic GenAI apps using LLMs Bachelors in Computer Science or similar technical degree PREFERRED QUALIFICATIONS Strong understanding of distributed system design, including: Load balancing, caching, and eventual consistency along with fault tolerance and high availability and API design principles (REST, GraphQL, gRPC) Extensive experience in designing, developing, and deploying scalable, enterprise-grade backend systems using a micro-services' architecture Hands-on with public or private Cloud Services and serverless architectures: Expertise in messaging systems such as SNS and SQS for event-driven architectures. Working knowledge of modern front-end frameworks, particularly React.js, to collaborate with front-end teams effectively. Proven experience in leading cross-functional teams and mentoring junior developers. Knowledge of IAM roles, security best practices, and cost optimization. Experience with containerization and orchestration using Docker and Kubernetes, including: Managing deployments, scaling strategies, and monitoring. Understanding of client-side state management, component lifecycle, and API integration. Ability to design vendor-neutral solutions to avoid cloud provider lock-in Experience in implementing observability using tools such as Prometheus, Grafana, and AWS CloudWatch. Expertise in CI/CD pipelines with tools such as GitHub Actions, Jenkins, or AWS CodePipeline. Strong focus on security, data privacy, and compliance. Exceptional problem-solving skills and the ability to break down complex requirements into actionable plans. Effective communicator with experience in stakeholder engagement, technical documentation, and presenting solutions to both technical and non-technical audiences. Commitment to software quality with experience in: Automated testing frameworks (e.g., JUnit, PyTest). Code reviews, version control (Git), and adherence to clean coding principles.

Responsibilities

You will drive the development and deployment of innovative AI models and systems that impact Apple's products and services. This includes implementing robust ML infrastructure and developing automated ML pipelines for rapid experimentation.