Machine Learning Engineer at Apple

Cupertino, California, United States -

Full Time

Start Date

Immediate

Expiry Date

27 May, 26

Salary

220900.0

Posted On

27 Feb, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

C++, C, Machine Learning, Neural Networks, K-Nearest Neighbors, Linear Algebra Kernels, Parallel Code, Multicore, Manycore, Cluster Platforms, Compiler Optimization, Assembly Language, Code Analyzers, Debuggers, Profilers, GDB Debuggers

Industry

Computers and Electronics Manufacturing

Description

Imagine what you can do here. Apple is a place where extraordinary people gather to do their lives best work. Together we create products and experiences people once couldn’t have imagined, and now, can’t imagine living without. It’s the diversity of those people and their ideas that inspires the innovation that runs through everything we do. DESCRIPTION APPLE INC has the following available in Cupertino, California and various unanticipated locations throughout the USA. Working with computer architects to develop ideas for improving performance on future silicon. Improving performance of machine learning algorithms on the CPUs in apple watches, iPhones and Mac. Testing workloads to ensure no performance regressions on silico. Debugging performance regressions on silicon and improve performance of machine learning model. Researching about instruction set architectures and conduct performance tuning on hardware. Collaborating with compiler teams to improve application and system performance. Working closely with OS teams to debug issues and maintain the operating system. Benchmarking and comparing the performance of workloads across different operating system/compiler/silicon versions. Working with machine learning teams to find ways to improve the performance of their models on the CPUs in different devices. Presenting CPU performance results to cross functional teams. Working with performance modeling team to develop plans for silicon performance profiling and characterization; and working with instruction profiling tools to develop new instructions to improve instruction time. 40 hours/week. At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $166,470 - $220,900/yr and your base pay will depend on your skills, qualifications, experience, and location. PAY & BENEFITS: Apple employees also have the opportunity to become an Apple shareholder through participation in Apple’s discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple’s Employee Stock Purchase Plan. You’ll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses — including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits: https://www.apple.com/careers/us/benefits.html. Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program. MINIMUM QUALIFICATIONS Master’s degree or foreign equivalent in Electrical Engineering, Computer Engineering or related field. Experience and/or education must include: Programming in C/C++ and machine learning including neural networks and K-nearest neighbors. Developing high performance software for linear algebra kernels and kernels used in machine learning applications. Write parallel code for multicore, manycore, and cluster platforms. Write parallel programs understanding machine performance characteristics and how hardware design affects software design. Optimizing compilers that effectively exploit modern processor architectures and implementing optimizations within the framework of a compiler. Knowledge of assembly language programming. Applying tools including compilers, code analyzers, debuggers, and profilers. Utilizing modern programming tools including GDB debuggers and x86 disassemblers. Evaluate performance and implement optimizations for machine learning algorithms using computer arithmetic, processor architecture, memory organization and management, concurrent computation. PREFERRED QUALIFICATIONS N/A

Responsibilities

This role involves working with computer architects to improve performance on future silicon, specifically by enhancing machine learning algorithms on CPUs across various Apple devices. Responsibilities include testing workloads, debugging performance regressions, researching instruction set architectures, and collaborating with compiler and OS teams.