Core ML Jobs in Computer Vision
Browse CV roles that require Core ML across all industries and experience levels.
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What is Core ML?
Core ML is Apple’s on-device inference framework, running models across the CPU, GPU and Neural Engine on iPhone, iPad and Mac. It is the required path for any vision feature shipping in an iOS application with acceptable performance and battery life.
Where Core ML is used
Consumer apps doing on-device recognition, AR features built on ARKit, fitness and form analysis, and privacy-sensitive applications where images must never leave the device.
Roles that ask for Core ML
- iOS Engineer, ML
- Mobile AI Engineer
- Computer Vision Engineer
- AR/VR Engineer
- Edge AI Engineer
Related skills & tools
Core ML jobs — common questions
How do PyTorch models reach Core ML?
Through coremltools, converting from traced PyTorch or ONNX. Conversion usually needs some work — unsupported operations, shape handling and quantisation settings — and validating numerical parity afterwards is standard practice.
What is the Neural Engine and can I target it directly?
Apple’s dedicated inference accelerator. You cannot target it explicitly; Core ML decides placement based on the model’s operations and precision. Structuring models so they stay on the Neural Engine rather than falling back to CPU is much of the optimisation work.
How does Core ML relate to the Vision framework?
Vision provides ready-made capabilities — face and text detection, body pose, tracking — and can also run Core ML models with image preprocessing handled for you. Many iOS features need no custom model at all.