Do you want to play a part in the next revolution in Foundation Models? Contribute to model hill climbing for Apple Intelligence features that leverage Apple Foundation Models, and work with the people who built the intelligent products that helps millions of people get things done - just by asking or typing! The vision for the AI/ML FM Data organization is to improve Foundation Models by leveraging data from a variety of sources: crawl, license, vendor and internal crowd-sourcing. As a Sr ML Engineering on the team, you will drive ML innovations, identify key opportunity areas where data can play a crucial role and experiment with various data augmentation strategies to improve model training efficiency and performance..
Description
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We are looking for people with a track record in building models and model-driven products to affect user experiences. Join us, and impact hundreds of millions of customers across billions of their interactions with foundation model powered Apple Intelligence features, that are available on iPhone, iPad, HomePod, Mac, Watch, CarPlay, and tv across more than 30 languages. - Algorithm development: Define signals that are important in prompts, responses and CoT reasoning steps. These usually require a fine-tuned model for specific use cases. - Model evaluation: Understand the importance of a balanced eval-set. Ability to perform error analysis to figure out how to improve model capabilities - Ablation experiments: Test your data augmentation strategies via ablation experiments. Comfortable debugging training errors, and tune hyper-parameters and data mixture to achieve desired outcome. - Data processing and data filtering: Ability to efficiently process and filter very large amounts of data, often times messy.
Minimum Qualifications
- 5+ years of hands on ML engineering experiences.
- Master or PhDs in Computer Science, Electric Engineering or Mathematics.
- Have prior experience as an ML modeler/scientist/researcher. Knowledgeable in classic machine learning algorithms (SVM, Random Forest, Naive Bayes, KNN etc), as well as comfortable with more modern deep learning frameworks (PyTorch, Tensorflow, Jax).
- Familiarity with multi-modal data and large models including image and video.
- Possess strong software engineering skills and mindset. Have a high bar for engineering code quality and scalability.
Preferred Qualifications
- Hands on experiences with different phases in LLM model training, including LoRA, SFT, RLHF, reward modeling.
- A good communicator with clear and concise, active listening and empathy skills.
- Are self-motivated and curious. Strive to continually learn on the job.
- Have demonstrated creative and critical thinking with an innate drive to improve how things work. Have a high tolerance for ambiguity.
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 $166,600 and $296,300, 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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