Software Engineer - ML Data at Apple

Cupertino, California, United States -

Full Time

Start Date

Immediate

Expiry Date

03 Feb, 26

Salary

0.0

Posted On

05 Nov, 25

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Machine Learning, Distributed Systems, Data Services, Cloud-Based Architectures, Performance Tuning, Debugging, Data Modeling, Data Architecture, Automation, CI/CD Tooling, PyTorch, TensorFlow, Problem Solving, Collaboration, Advertising Industry Experience

Industry

Computers and Electronics Manufacturing

Description

At Apple, we focus deeply on our customers’ experience. Apple Ads brings this same approach to advertising, helping people find exactly what they’re looking for and helping advertisers grow their businesses. Our technology powers ads and sponsorships across Apple Services, including the App Store, Apple News, and MLS Season Pass. Everything we do is designed for trust, connection, and impact: We respect user privacy, integrate advertising thoughtfully into the experience, and deliver value for advertisers of all sizes—from small app developers to big, global brands. Because when advertising is done right, it benefits everyone. DESCRIPTION The ML Platform team is responsible for bringing numerous features to advertisers and consumers while simultaneously supporting scalable modeling and continuous experimentation by all Ads teams. As a key contributor to this team, you will design and develop secure and scalable back-end systems. You will enjoy building high-performing, elegant systems from the ground up, in close partnerships with various teams. You will also possess keen judgment in selecting technologies and building the right solution for the interesting challenges we get to tackle here. You will have the opportunity to define and refine architectures to meet the unique ad network challenges we must solve. You will play a meaningful role building machine learning products which deliver on Apple's privacy commitments and change the way advertising works with data. Join us and contribute to a culture that emphasizes reliability, simplicity, and scalability. You will join a team of world-class machine learning engineers hungry to apply leading-edge technologies to deliver extraordinary experiences to our customers. We are one team, nurturing each other’s growth and supporting each other in delivering for our customers! MINIMUM QUALIFICATIONS Experience writing mission-critical code for production machine learning systems. Experience building production data services/pipelines using distributed processing systems like Spark. Experience with distributed systems (e.g Ray, Spark, Kubernetes). Experience working on distributed systems where scalability and performance are critical. Experience building AI/ML tooling and/or data infrastructure for AI/ML. Experience building and scaling cloud-based architectures. Experience performance tuning & trouble-shooting. Strong problem solving and debugging skills. Strong data modeling and data architecture skills. Pride in building automation and development tools. Familiarity with CI/CD tooling. PREFERRED QUALIFICATIONS PhD in Computer Science with 2+ years contributing to production machine learning systems, or MS in CS with 4+ years of engineering experience and 2+ years contributing to production machine learning systems, or (c) BS in CS with 5+ years of engineering experience and 2+ years contributing to production machine learning systems. Ability to communicate effectively, both written and verbal, with technical and non-technical multi-functional teams Results oriented with a desire to work in a fast-paced and collaborative work environment Experience building production machine learning models using frameworks like PyTorch, TensorFlow is highly desired Prior experience in advertising industry is a huge plus

Responsibilities

You will design and develop secure and scalable back-end systems for the ML Platform team. You will build machine learning products that align with Apple's privacy commitments and enhance advertising experiences.