Wi-fi Ai/ml Software Engineer, Wireless Technologies & Ecosystems

Apple Apple · Big Tech · Cupertino, CA · Software and Services

This role focuses on applying AI/ML to Wi-Fi software for Apple products, optimizing performance, predicting congestion, and enhancing connection reliability. The engineer will design and implement ML models, apply AI to internal tools, analyze network data, and optimize models for on-device inference. The role involves collaboration with hardware and software teams, and a strong understanding of networking protocols and wireless standards is required.

What you'd actually do

  1. Design and implement machine learning models that optimize Wi-Fi performance, predict network congestion, and enhance connection reliability
  2. Apply AI and machine learning technologies to internal development tools and workflows, creating intelligent systems that improve software quality, accelerate debugging, and enhance engineering productivity
  3. Collaborate with cross-functional teams to integrate AI-driven networking features into system architecture and hardware platforms
  4. Analyze large-scale network telemetry data to identify patterns, anomalies, and opportunities for ML-based improvements
  5. Optimize ML models for on-device inference, balancing accuracy with power consumption and computational constraints

Skills

Required

  • BS degree in Computer Science, Electrical Engineering, Computer Engineering, or equivalent field
  • 4+ years of professional experience in Wi-Fi, wireless networking, or related networking technologies
  • strong programming skills in C/C++ or Python
  • demonstrated experience with machine learning frameworks and applying ML techniques to real-world problems
  • deep understanding of networking protocols (TCP/IP, routing, etc.) and wireless standards (802.11a/b/g/n/ac/ax)
  • excellent communication and collaboration skills

Nice to have

  • MS or PhD in Computer Science, Electrical Engineering, or related field with focus on networking or machine learning
  • experience with on-device ML optimization and deployment on resource-constrained systems
  • published research or patents in wireless networking or applied machine learning
  • demonstrated familiarity with network simulation tools and large-scale data analysis
  • strong track record of shipping production-quality networking or ML-enabled products

What the JD emphasized

  • shipping software features
  • on-device inference
  • shipping production-quality networking or ML-enabled products

Other signals

  • shipping software features
  • optimize ML models for on-device inference
  • researching emerging wireless technologies and AI techniques