ML Platform Engineer for Scalable Ads

Apple, Inc.; New York (NY); On-site; USD 185,000 - 278,000; Full time

Benefits offered by this job

Stock options

Relocation assistance

Health and dental coverage

Education reimbursement

Job summary

Apple Ads ML Platform Team is seeking a results-driven engineer to design and build secure, scalable back-end systems that power advertising features across Apple platforms. You will collaborate with ML engineers and data scientists to deploy models, manage data pipelines, and deliver high-performance services with strong privacy protections.

You will work on embedding management, feature stores, and distributed processing for production ML workloads at scale, influencing how advertisers and

Qualifications

• Experience writing mission-critical code for production ML systems.
• Experience building ML infrastructure, frameworks or services used by multiple teams.
• Experience building or operating feature stores, or comparable ML data infrastructure serving production models.
• Experience with embedding management: generating and versioning embeddings, refresh and retirement policy, and storing and serving them for retrieval at scale.
• Strong understanding of the ML lifecycle: training, evaluation, deployment and serving/inferencing, with working experience building and deploying models.
• Understanding of model evaluation, train-serve skew and data drift.
• Working knowledge of deep learning architectures and training frameworks such as PyTorch or TensorFlow.
• Prior experience applying ML at scale in advertising, recommender systems, information retrieval or related domains.
• Experience with training data generation across multi-modal data (text, image and structured), including sampling and point-in-time correctness.
• Experience building production data pipelines for ML systems where scale and performance are critical using distributed processing systems.
• Experience building ML systems using batch and streaming deployments, workflow orchestration and modern storage formats.
• Strong data modeling and data architecture skills, with a high bar for system and data quality: correctness, reliability, testing and validation.
• Strong problem solving, debugging and performance tuning skills, and pride in building automation, tooling and CI/CD.
• Results oriented, with the ability to communicate effectively, both written and verbal, with technical and non-technical multi-functional teams.
• Product-minded with a proven ability to seek projects with a sense of ownership

Responsibilities

• Design and develop secure, scalable back-end systems for ML platform.
• Collaborate with ML engineers and scientists to deploy models and manage data pipelines.
• Build end-to-end ML features and services for advertisers.
• Improve privacy-preserving ML and compliance across systems.

Skills

ML production

ML infrastructure

Feature stores

Embeddings management

ML lifecycle

Model evaluation

PyTorch

TensorFlow

Ad tech ML

Multimodal data

Data pipelines

Distributed systems

CI/CD

Communication

Ownership

Education

PhD in Computer Science or related field

MS in Computer Science or related field

BS in Computer Science or related field

Tools

PyTorch

TensorFlow

Airflow

Job description

Apple Ads ML Platform Team is seeking a results-driven engineer to design and build secure, scalable back-end systems that power advertising features across Apple platforms. You will collaborate with ML engineers and data scientists to deploy models, manage data pipelines, and deliver high-performance services with strong privacy protections.

You will work on embedding management, feature stores, and distributed processing for production ML workloads at scale, influencing how advertisers and