Job Information
Apple Cellular 4G/5G Firmware Data Science & Machine Learning Engineer in Sunnyvale, California
Cellular 4G/5G Firmware Data Science & Machine Learning Engineer
Sunnyvale,California,United States
Hardware
Do you have a passion for invention and self-challenge? Do you thrive with pushing the limits of what’s considered feasible? As part of a world class modem team, you’ll craft sophisticated innovative embedded firmware that deliver more performance in our products than ever before! You’ll work across subject areas to transform improved hardware elements into a single, coordinated design. Join us, and you’ll help us innovate new wireless systems technologies that continually outperform the previous iterations. By collaborating with other product development groups across Apple, you’ll push the industry boundaries of what wireless systems can do and improve the product experience for our customers across the world. Do you want to have an impact on every single Apple product? As a Cellular 4G/5G Firmware Data Science & Machine Learning Engineer, you will be at the center of the embedded 5G/4G/multimode cellular firmware effort within a silicon design group responsible for crafting and productizing groundbreaking cellular SoCs.
Description
Data Science & Machine Learning Engineer will be responsible for developing state-of-the-art data processing pipeline based on machine learning models and leveraging data science algorithms to parse substantial data and logs in timely manner to automatically tackle the issues or provide recommendations for the next step of solving problem. In addition, you will be closely partnering with FW engineering teams in integrating and deploying ML models and data processing pipeline as part of entire automation system to deliver analysis results to benefit FW engineers in debugging issues. You will work with an amazing team, brainstorm new insights, and develop models and algorithms to solve complicated problems that have a significant impact.
Minimum Qualifications
Master’s degree in Data Science or Computer Science
Proficient Python developer with 3+ years proven programming skills using standard ML tools such as PyTorch, Tensorflow, HuggingFace
Good understanding of machine learning, deep learning (including LLMs) and natural language processing and ability to optimize machine learning models to adapt to solving various kinds of issues
Hands on experience in implementing end-to-end machine learning projects
Ability to think creatively and identify, build, and support solutions and roadmaps focused on automation and reduction of manual processes
Key Qualifications
Preferred Qualifications
Ph.D. degree in Data Science or Computer Science
Proficient Python developer with 5+ years validated programming skills using standard ML tools such as PyTorch, Tensorflow, HuggingFace
Proven understanding of machine learning, deep learning (including LLMs) and natural language processing and ability to optimize machine learning models to adapt to solving various kinds of issues
Experience in developing machine learning models and /or deep learning models, feature engineering and rich experience in implementing end-to-end machine learning projects
Experience in using analytics and statistical methods to transform data into useful insights and actionable results
Experience with relational database (e.g Postgres), SQL and non-relational database (e.g.Mango DB)
Ability to think creatively and identify, build, and support solutions and roadmaps focused on automation and reduction of manual processes
Strong critical thinking and interpersonal skills with the ability and desire to learn and evaluate new technologies
Education & Experience
Additional Requirements
Pay & Benefits
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 (https://www.apple.com/careers/us/benefits.html) 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 take affirmative action to ensure 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. (https://www.eeoc.gov/sites/default/files/2023-06/22-088_EEOC_KnowYourRights6.12ScreenRdr.pdf)
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Apple is an equal opportunity employer that is committed to inclusion and diversity. We take affirmative action to ensure 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 (Opens in a new window) .
Apple will not discriminate or retaliate against applicants who inquire about, disclose, or discuss their compensation or that of other applicants. United States Department of Labor. Learn more (Opens in a new window) .
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