Job 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 solutions for the unique ad network challenges we face. 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! Experience writing mission-critical code for production machine learning systems Experience building ML infrastructure, frameworks or services used by multiple teams Experience building SDKs, API, and automation UIs used by development teams Proven experience building automation and CI/CD Passionate about improving the developer experience for AI/ML practitioners Solid understanding of the ML lifecycle: training, evaluation, deployment and serving/inferencing, with working experience building and deploying models Solid 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 Strong problem solving, debugging and performance tuning skills 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 Experience in advertising industry Experience with distributed training and/or optimizing large-scale models for low-latency serving Experience building infrastructure for diverse sets of model development use cases including LLMs, multimodal models, classical ML, and reinforcement learning. Experience building and/or operationalizing foundation models Experience with agentic AI Prior experience in privacy-preserving ML Education & Experience PhD in Computer Science or related field with 3+ years of engineering experience and 5+ years of machine learning experience; or MS in Computer Science or related field with 6+ years of engineering experience and 5+ years of machine learning experience; or BS in Computer Science or related field with 7+ years of engineering experience and 5+ years of machine learning experience

Requirements

Must-haves

Experience writing mission-critical code for production machine learning systems
Experience building ML infrastructure, frameworks or services used by multiple teams
Experience building SDKs, API, and automation UIs used by development teams
Proven experience building automation and CI/CD
Passionate about improving the developer experience for AI/ML practitioners
Solid understanding of the ML lifecycle: training, evaluation, deployment and serving/inferencing, with working experience building and deploying models
Solid 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
Strong problem solving, debugging and performance tuning skills
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
Experience in advertising industry
Experience with distributed training and/or optimizing large-scale models for low-latency serving
Experience building infrastructure for diverse sets of model development use cases including LLMs, multimodal models, classical ML, and reinforcement learning.
Experience building and/or operationalizing foundation models
Experience with agentic AI
Prior experience in privacy-preserving ML
Education & Experience

Nice-to-haves

None flagged.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

mlmachine learningapici/cdai

Platform: apple
Effort: medium