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Senior Staff Machine Learning Engineer, ML Platform

Apple· Software and Services
Apply on company site
Hybrid (Cupertino, CA and New York City, NY)$262.5k - $394kfull-timePosted 3w ago

About the role

Senior ML Platform role focused on building a self-serve, unified platform for model training, inference, and agentic AI to empower Apple Ads teams to develop, deploy, and operate ML applications at scale while upholding privacy commitments.

Responsibilities

  • Experience building shared ML platforms, frameworks or services used by multiple teams or organizations.
  • Deep understanding of the ML lifecycle, including training pipelines, evaluation methodologies, and deployment patterns.
  • Deep understanding of deep learning architectures (Transformers, LLMs, DNNs) and training frameworks (TensorFlow, PyTorch)
  • Prior experience applying ML at scale in Ads, recommender systems, information retrieval or related domains.
  • Prior experience in distributed training at scale and optimization techniques like model pruning, compression, quantization & distillation.
  • Prior experience building AI/ML tooling for model fine-tuning and training, and/or infrastructure at scale
  • Ability to communicate effectively, both written and verbal, with technical and non-technical multi-functional teams
  • Results oriented with strong technical leadership skills and a desire to work in a fast-paced collaborative work environment
  • Curious business attitude with a proven ability to seek projects with a sense of ownership.
  • Prior experience in privacy-preserving ML using techniques such as federated learning and differential privacy
  • Experience with LLM training and inference — pre-training, SFT, verifiable RL rewards, inference-Familiarity with Agentic AI
  • PhD/MS/BS in Computer Science or related field with 10+ years of industry experience in building ML systems

Qualifications

  • PhD/MS/BS in Computer Science or related field with 10+ years of industry experience in building ML systems
  • Prior experience in privacy-preserving ML using techniques such as federated learning and differential privacy
  • Experience with LLM training and inference — pre-training, SFT, verifiable RL rewards, inference-Familiarity with Agentic AI
  • Deep understanding of deep learning architectures (Transformers, LLMs, DNNs) and training frameworks (TensorFlow, PyTorch)
  • Prior experience applying ML at scale in Ads, recommender systems, information retrieval or related domains
  • Prior experience in distributed training at scale and optimization techniques like model pruning, compression, quantization & distillation

Skills

Required:ML Platform developmentML lifecycleDeep learning architecturesTraining frameworksDistributed training at scaleCommunication
Nice to have:Privacy-preserving MLLLM training and inference

Benefits

  • Comprehensive medical and dental coverage
  • retirement benefits
  • discounted products and free services
  • educational expense reimbursement including tuition
  • potential discretionary bonuses or commission payments and relocation assistance
  • Apple shareholder opportunities via stock programs
Last updated Oct 2, 2026. Interested? Apply on the company site.

About Apple

Discover the innovative world of Apple and shop everything iPhone, iPad, Apple Watch, Mac, and Apple TV, plus explore accessories, entertainment, and expert device support.

Discover the innovative world of Apple and shop everything iPhone, iPad, Apple Watch, Mac, and Apple TV, plus explore accessories, entertainment, and expert device support.

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