Description

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

Pay & Benefits

At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $147,400 and $272,100, and your base pay will depend on your skills, qualifications, experience, and location.

Apple employees also have the opportunity to become an Apple shareholder through participation in Apple's discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple's Employee Stock Purchase Plan. You'll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses - including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits.

Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.

Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant .