On-Device Vision ML Engineer: Video CV

Apple Inc.; Sunnyvale (CA); Hybrid; USD 150,000 - 278,000; Full time

Job summary

Apple Inc. is seeking a Machine Learning Systems Engineer in Sunnyvale, CA to ship cutting-edge computer vision on Apple devices. You will train, evaluate, and deploy purpose-built vision models under strict on-device constraints.

You will optimize performance, evaluate power and thermal metrics, and collaborate with hardware/AI teams to deliver Apple-quality experiences across the stack.

Qualifications

• Bachelor’s degree in Computer Science, ML, or related discipline and 3+ years of industry experience.
• Proven track record of production-quality code for on-device CV/ML features on embedded platforms.
• Strong knowledge of OS fundamentals and programming in Python and C++.
• Hands-on experience with PyTorch and end-to-end ML lifecycle (data processing, training, evaluation, edge deployment).
• Experience with SFT pipelines to adapt vision and multimodal models for on-device tasks.
• Solid understanding of ML architectures, especially Multimodal LLMs and integration into production systems.

Responsibilities

• Develop on-device software bridging multimodal AI models with production systems on Apple devices.
• Optimize on-device inference latency, memory footprint, and computation for CV/ML models.
• Benchmark and profile power consumption and thermal performance on Apple silicon.
• Collaborate with cross-functional teams to capture requirements and design maintainable CV systems.
• Design experiments to understand on-device deployment tradeoffs and inform system design.
• Debug concurrent embedded systems and develop tools/visualizations when needed.

Skills

Python

C++

PyTorch

On-device ML

Embedded systems

ML deployment

SFT pipelines

Multimodal LLMs

Education

Bachelor’s degree in Computer Science or related

Tools

Git

Linux

Job description

Apple Inc. is seeking a Machine Learning Systems Engineer in Sunnyvale, CA to ship cutting-edge computer vision on Apple devices. You will train, evaluate, and deploy purpose-built vision models under strict on-device constraints.

You will optimize performance, evaluate power and thermal metrics, and collaborate with hardware/AI teams to deliver Apple-quality experiences across the stack.