SW ML Optimization Engineer

Socket.dev; Cupertino (CA); On-site; USD 180,000 - 240,000; Full time

Job summary

Apple seeks a performance-focused engineer to analyze workloads on Apple Silicon, identify bottlenecks, and recommend optimizations. You will work with hardware and software teams to improve performance across the platform, leveraging expertise in GPU programming and profiling tools.

You will collaborate with engineers to address challenges, contribute to prototype systems, and help drive next-generation silicon features and software integration.

Qualifications

• Bachelor's degree in CS/CE or related quantitative field; equivalent practical experience.
• Experience with GPU or parallel programming using Metal/OpenCL/CUDA or similar.
• Experience with profiling/ performance analysis tools and concepts.
• Development experience in Python, C or C++.

Responsibilities

• Analyze workloads to identify performance bottlenecks in hardware and software.
• Propose optimizations and drive improvements for Apple Silicon.
• Collaborate with developers across teams to provide feedback to silicon and software teams.

Skills

GPU/parallel programming

Profiling tools

Python

C/C++

Metal

Education

Bachelor's degree in Computer Science/Engineering or related field

Tools

Xcode Instruments

VTune

Nsight Compute

Job description

At Apple, our Platform Architecture group is responsible for connecting our hardware and software into one unified system. You’ll collaborate with engineers across Apple to design how all of our technologies work in unison, drive development of our renowned system-on-a-chip architecture and develop forward-looking prototype systems and software.

Description

Our team is driving performance enhancements in application and system software and developing novel algorithms to deliver integrated, highly optimized solutions based on Apple Silicon. In this role, you will analyze existing and new workloads to identify performance bottlenecks in the hardware and/or software. Working with your colleagues, you will address performance limitations and provide recommendations for Apple hardware and software improvements. In addition to working directly with developers, you will identify patterns of performance challenges on Apple silicon, emerging new usage models, and provide feedback to the silicon and software teams for potential improvements.

Minimum Qualifications

• Bachelor's degree in Computer Science, Computer Engineering, Mathematics, Electrical Engineering, or a related quantitative field (or equivalent practical experience).
• Experience with GPU or parallel programming—e.g., Metal, OpenCL, CUDA, or similar—through coursework, personal projects, internships, or research.
• Experience with profiling/performance analysis tools (e.g., Xcode Instruments, VTune, Nsight Compute, or equivalent) and basic performance analysis concepts.
• Development experience in Python, C or C++.

Preferred Qualifications

• Solid foundation in mathematics, algorithms, and/or computer architecture fundamentals.
• Experience writing or tuning compute kernels (e.g., GEMM, attention, or other numerically intensive routines).
• Exposure to ML frameworks such as PyTorch, and to AI/ML, graphics, or HPC workloads and benchmarks.
• Coursework or projects involving parallel computing, numerical methods, signal processing, or performance optimization.
• Interest in (or exposure to) the deeper stack — drivers, firmware, compilers, or low-level libraries.
• Interest in Apple Silicon and its frameworks (Metal, MLX, Core ML).
• Curiosity about hardware/software co-design and a demonstrated drive to learn independently.
• Strong communication skills and the ability to collaborate effectively across teams.