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Staff ML Engineer - Ads ML Infrastructure

Apple· Machine Learning Platform
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Cupertino, CA, New York, NY$184.7k - $324.8kfull-timePosted 3mo ago

About the role

Staff ML Engineer focusing on Ads ML Infrastructure within Apple’s Ad Platforms group. Lead the design, development, and optimization of large-scale ML serving platforms, low-latency real-time and batch inference, and ML tooling to support privacy-preserving advertising features. Collaborate with engineers and data scientists in an Agile environment to build scalable back-end systems and improve ML models and applications for advertisers and consumers.

Responsibilities

  • Design and operate large-scale, low-latency ML Serving platform supporting real-time and batch inference.
  • Evaluate and adopt model quantization, tensor parallelism, and inference optimizations (e.g., ONNX Runtime, TensorRT, vLLM).
  • Work on distributed systems (e.g., Ray, high-throughput RPC) to support scalable inference workloads and hybrid online/offline serving patterns.
  • Design and optimize low-level GPU kernels to maximize hardware utilization and accelerate deep learning primitives.
  • Leverage experience in advertising, federated learning, and privacy-preserving ML techniques.
  • Mentor and lead by example through code/design reviews, working groups, and knowledge sharing.
  • Develop foundational AI/ML platforms and tooling (Feature Stores, Vector DB) to accelerate productivity and model lifecycle management.
  • Perform performance tuning and troubleshooting.
  • Build developer-oriented abstractions and automation to streamline ML workflows and reduce operational burden.
  • Communicate effectively with multi-functional teams (technical and non-technical).
  • Deliver results in a fast-paced, collaborative environment.

Qualifications

  • PhD, MS, or BS in computer science or a related field, with 8+ years of experience in machine learning and strong software engineering skills.

Skills

Required:Large-scale ML serving and deploymentModel optimization and quantizationDistributed systems for MLLow-level GPU kernel optimizationLeadership and mentoringML platform tooling
Nice to have:Privacy-preserving ML / federated learning

Benefits

  • Comprehensive medical and dental coverage
  • retirement benefits
  • range of discounted products and free services
  • reimbursement for certain educational expenses (tuition)
  • discretionary bonuses or commission payments possible
  • relocation assistance (if applicable)
  • employee stock programs (RSUs)
Last updated Aug 14, 2026. Interested? Apply on the company site.

About Apple

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