Machine Learning Systems Engineer, Video Computer Vision

What you'll do

• Develop on-device software to bridge multimodal AI models with production systems on Apple devices.
• Optimize inference latency, memory footprint, and computational efficiency for CV/ML models.
• Benchmark and profile power consumption and thermal performance on Apple silicon.
• Design experiments to evaluate quality and on-device deployment tradeoffs for system design decisions.
• Debug concurrent systems on embedded devices using existing and custom-built tools.
• Train, evaluate, and deploy purpose-built vision models on Apple hardware.
• Implement Supervised Fine-Tuning pipelines to adapt foundation models for specialized on-device tasks.

What we're looking for

• Bachelor’s degree in Computer Science, Machine Learning, or a related discipline.
• 3+ years of relevant industry experience.
• Strong machine learning fundamentals and understanding of multimodal LLM architectures.
• Proven track record of writing high-quality production code for shipped on-device CV/ML features on embedded platforms.
• Extensive programming experience in Python and C++.
• Solid understanding of operating system fundamentals.
• Hands-on experience with PyTorch and the end-to-end ML lifecycle.
• Experience with Supervised Fine-Tuning (SFT) pipelines for vision and multimodal foundation models.
• Programming experience with Swift and familiarity with CoreML, CoreFoundation, and RealityKit frameworks (preferred).
• Fundamental knowledge of real-time video pipelines, image transformations, and rendering loops (preferred).
• Experience optimizing models for neural network accelerators like Apple Neural Engine or mobile GPUs (preferred).