Machine Learning Systems Engineer

Responsibilities

• Train, evaluate, and deploy computer vision models on Apple hardware.
• Develop techniques to optimize model performance, efficiency, and scalability under on-device constraints.
• Write production code for shipped on-device computer vision and machine learning features on embedded platforms.
• Build and use supervised fine-tuning pipelines for vision and multimodal foundation models.
• Integrate machine learning components into complex production systems.
• Optimize models for neural network accelerators such as the Apple Neural Engine and mobile GPUs.

Requirements

• Bachelor’s degree in Computer Science, Machine Learning, or a related discipline.
• At least 3 years of relevant industry experience.
• Strong machine learning fundamentals and understanding of multimodal large language models.
• Production programming experience with Python and C++.
• Hands-on experience with PyTorch and the end-to-end machine learning lifecycle, including data preprocessing, training, evaluation, and edge deployment.
• Experience with supervised fine-tuning pipelines for specialized on-device downstream tasks.
• Experience delivering on-device computer vision or machine learning features on embedded platforms.
• Preferred: programming experience with Swift and familiarity with CoreML, CoreFoundation, and RealityKit.
• Preferred: knowledge of real-time video pipelines, image transformations, rendering loops, and neural network accelerator optimization.