Embedded Signal Processing and ML Algorithms Engineer

Apple

3+ Years | Sunnyvale, California, United States (On Site) | Full Time | 4 months ago

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Job Summary

Join HID sensing and interaction algorithms team developing advanced sensing algorithms for user experiences on Mac, iPhone, iPad, Apple Pencil, Apple Watch, and new products. Seeking an algorithm engineer to work in cross-disciplinary teams across a full product cycle. The team collaborates at the intersection of hardware, software, and design, tackling diverse problems with specialists from various fields. The role involves designing, developing, and supporting high-quality, scalable algorithm implementations and data processing pipelines to enable rapid algorithm development and analysis for Apple products.

Must Have

BS and 3 years of relevant industry experience
C/C++ and Python programming skills
Experience with embedded systems or resource-constrained environments for algorithm implementation

Good to Have

MS (PhD preferred) with 2+ years of experience in developing, optimizing, and implementing complex algorithms
Experience with object-oriented programming and common design patterns
Optimizing and implementing complex algorithms on resource-constrained platforms
Background in numerical methods and techniques, especially for real-time DSP algorithm stability
Knowledge of fundamental DSP concepts (Adaptive filtering, linear algebra, machine learning, statistics)
Excellent communication, presentation, and documentation skills

Perks & Benefits

Discretionary employee stock programs
Discretionary restricted stock unit awards
Discounted Apple stock purchase
Comprehensive medical and dental coverage
Retirement benefits
Discounted products and free services
Reimbursement for certain educational expenses (tuition)
Discretionary bonuses or commission payments
Relocation assistance

Job Description

Join HID sensing and interaction algorithms team that develops advanced sensing algorithms which enable the best-in-the-world user experiences for Mac, iPhone, iPad, Pencil, Watch, and exciting new products. We are looking for an algorithm engineer who could work well in cross-disciplinary teams over a full product cycle. Our team comes from diverse backgrounds in signal and image processing, statistics, machine learning, controls, physics, firmware and software development, neuroscience, human factors, and more dedicated to inventing new ways of interacting with Apple products and shipping amazing products to millions of users every year. The team operates at the intersection of hardware, software, and design. This means that the wide variety of problems you will solve have many interesting facets and you will get to work with specialists from all across Apple.

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We are looking for a Algorithms engineer who can write efficient and scalable C / C++ code to perform signal processing in multiple compute environments. You will work with other algorithm engineers to analyze and validate algorithm prototypes. You will then architect and code the algorithm implementation, often targeting embedded or resource-constrained systems. You will work with system and firmware engineers to integrate your code into the product, but will take special responsibility for the algorithm implementation. You will also help us architect, develop, and optimize data processing and machine learning frameworks. This is a role where you will design, develop, and support high quality, scalable algorithm implementations and data processing pipelines that enable rapid algorithm development, analysis, and implementation for Apple products.

BS and a minimum of 3 years relevant industry experience.
Programming skills in C/C++ and Python.
Experience with embedded systems or resource constraint environments for algorithm implementation.

MS (Phd preferred) with 2+ years of experience in developing, optimizing and implementing complex algorithms.
Experience with object-oriented programming and common design patterns.
Optimizing and implementing complex algorithms on resource constrained platforms with a background in numerical methods and techniques, especially as relates to stability in real-time DSP algorithms.
Knowledge of fundamental DSP concepts such as Adaptive filtering, linear algebra, machine learning or statistics.
Excellent communication, presentation, and documentation skills.

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 $143,100 and $264,200, and your base pay will depend on your skills, qualifications, experience, and location.

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.

Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.

Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant.

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11 Skills Required For This Role

Communication Design Patterns Cpp Unity Game Texts Html Prototyping Python Algorithms Linear Algebra Machine Learning

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