Machine Learning Engineer at Apple

New York, New York, United States -

Full Time

Start Date

Immediate

Expiry Date

27 May, 26

Salary

220900.0

Posted On

27 Feb, 26

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Python, PyTorch, Machine Learning Models, NLP, Transformer-based Architectures, BERT, GPT, Statistical Modeling, Probabilistic Modeling, Bayesian Inference, Hypothesis Testing, A/B Tests, Multivariate Experiments, Scikit-learn, NLTK, Time-series Data Analysis

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 New York, New York. Work with Product, Design, Project and Engineering to identify, conceptualize and implement the ML use cases for Apple Sports. Prototype ML and Probabilistic algorithms specific to Sports Data. Analyze the Apple Sports Signals and recognize the relevant probabilistic patterns to enhance existing systems while keeping user privacy intact. Execute Statistical tests to identify strength and weakness of ML systems and address by using appropriate ML techniques. Find patterns in the data to enhance the user experience. Document and keep the Apple Sports teams up to date with ML research. 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 $147,400 - $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 Computer Science, Software Engineering, Electrical and Computer Engineering, or related field. Experience and/or education must include: Utilizing Python and PyTorch to design, train, and deploy machine learning models for prediction, classification, and generation tasks. Utilizing modern NLP techniques with Transformer-based architectures including BERT or GPT for text classification and generation. Applying statistical and probabilistic modeling, including logistic regression, Bayesian inference, and hypothesis testing, to support model development and evaluation. Designing and executing A/B tests and multivariate experiments to validate machine learning model performance and guide iterative improvements. Using Scikit-learn, including decision trees, clustering, and ensemble methods to implement classical machine learning algorithms Utilizing NLTK or similar NLP toolkits for text preprocessing, tokenization, sentiment analysis, and named entity recognition. Conducting time-series data analysis and pattern recognition using supervised and unsupervised learning techniques. Using version-controlled scripts and model evaluation frameworks to develop and maintain reproducible machine learning workflows. Documenting ML research findings and translating experimental results into actionable technical improvements. Collaborating cross-functionally with engineering, product, and design teams to integrate ML models into user-facing applications. PREFERRED QUALIFICATIONS N/A

Responsibilities

The role involves collaborating with cross-functional teams to identify, conceptualize, and implement Machine Learning use cases for Apple Sports, focusing on prototyping algorithms specific to sports data. Responsibilities also include analyzing data patterns, executing statistical tests to evaluate ML systems, and documenting research findings for the team.