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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Sr Machine Learning Engineer - ML Data - **Company:** Apple Inc. - **Location:** Cupertino, CA, United States - **Experience:** Expert - **Salary:** $184,700.0 - **Contract:** Permanent contract - **Skills:** Training Data, Continuous Integration, Data Architecture, Data Infrastructure, Software Debugging, Distributed Computing Environment, Information Retrieval, Machine Learning, Operational Databases, Performance Tuning, Recommender Systems, Tensorflow, Azure Machine Learning, Management of Software Versions, Workflow Management Systems, Pytorch, Large Language Models, Deep Learning, Model Validation, Information Technology, Machine Learning Operations, Data Generation - **Published:** September 17, 2026 - **Apply:** https://www.jobmonkeyjobs.com/career/28025758/Sr-Machine-Learning-Engineer-Ml-Data-California-Cupertino-7413 ## About the Role Experience writing mission-critical code for production machine learning 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 Solid 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 Preferred Qualifications Preferred Qualifications Experience in advertising industry Experience with LLM-based data generation or evaluation Familiarity with large-scale distributed training and its demands on data infrastructure Prior experience in privacy-preserving ML Familiarity with agentic AI, 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 ## Description The Apple Ads Machine Learning Platform team's mission is to empower Ads teams to build and scale the innovative ML systems that deliver highly optimized advertising content to consumers. Are you a results-oriented and versatile engineer who can excel in a fast-paced environment? You will work closely with ML engineers and scientists to design, develop, and build world-class platform capabilities that will enable Ads teams to improve and scale our ML features, models, and applications., 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. ## Related Videos - [Getting Started with Machine Learning](https://www.wearedevelopers.com/videos/260-getting-started-with-machine-learning) - [Introduction to Azure Machine Learning](https://www.wearedevelopers.com/videos/368-introduction-to-azure-machine-learning) - [Machine learning in the browser with TensorFlowjs](https://www.wearedevelopers.com/videos/155-machine-learning-in-the-browser-with-tensorflowjs) - [Photonic Computing: Programming a New Class of AI Accelerators (incl. Live Coding)](https://www.wearedevelopers.com/videos/100196-photonic-computing-programming-a-new-class-of-ai-accelerators-incl-live-coding) - [Geometric deep learning for drug discovery](https://www.wearedevelopers.com/videos/264-geometric-deep-learning-for-drug-discovery) - [30 Golden Rules of Deep Learning Performance](https://www.wearedevelopers.com/videos/11-30-golden-rules-of-deep-learning-performance) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models) - [How machine learning can help us tell fact from fiction](https://www.wearedevelopers.com/magazine/509-how-machine-learning-can-help-us-tell-fact-from-fiction) - [MLOps – What’s the deal behind it?](https://www.wearedevelopers.com/magazine/125-mlops-what-s-the-deal-behind-it) - [MLops – Deploying, Maintaining And Evolving Machine Learning Models in Production](https://www.wearedevelopers.com/magazine/115-mlops-deploying-maintaining-and-evolving-machine-learning-models-in-production) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development)