Multimodal Sensor Fusion Engineer - Edge AI

Apple Inc.; Sunnyvale (CA); On-site; USD 150,400 - 277,600; Full time

Benefits offered by this job

Employee stock plan

Medical and dental coverage

Tuition reimbursement

Relocation assistance

Job summary

Apple Inc. in Sunnyvale, California, seeks a Machine Learning Engineer to design and implement multimodal fusion algorithms for edge deployment, collaborating with hardware, software, and UX teams to deliver production‑ready models that delight users at scale.

The role emphasizes translating cutting‑edge research into scalable solutions, optimizing for on‑device inference, and driving best practices across the CVML team while shaping next‑generation products for millions of daily users.

Qualifications

• B.S. degree and 3 years of experience in software engineering, deep learning, sensor fusion, or related fields.
• Experience in deep learning frameworks such as PyTorch.

Responsibilities

• Leading the development of cutting‑edge multimodal fusion algorithms and taking ideas from concept to shipping
• Driving cross‑functional collaboration to understand algorithmic constraints, dependencies, and technical trade‑offs
• Partnering with engineers and designers to architect proof‑of‑concepts and prototype novel hardware for innovative applications
• Leading technical discussions and preparing presentations, papers, and talks to communicate your inventions and establish thought leadership
• Establishing coding standards, best practices, and technical strategies for your team

Skills

Software engineering

Deep learning

Sensor fusion

PyTorch

Education

B.S. degree

Job description

Apple Inc. in Sunnyvale, California, seeks a Machine Learning Engineer to design and implement multimodal fusion algorithms for edge deployment, collaborating with hardware, software, and UX teams to deliver production‑ready models that delight users at scale.

The role emphasizes translating cutting‑edge research into scalable solutions, optimizing for on‑device inference, and driving best practices across the CVML team while shaping next‑generation products for millions of daily users.