Apple Inc.
Cupertino, California, United States Software and Services
Description The Special Projects team at Apple is developing novel user-facing conversational features that leverage the multimodal capabilities of state-of-the-art foundation models. We are looking for a highly skilled Machine Learning Engineer to build the processes to evaluate these experiences. A successful candidate is experienced in evaluating complex foundation model driven systems end-to-end, translating subjective product requirements into objective criteria, and has strong statistical analysis skills.
Responsibilities
Design and implement processes for evaluating multi-modal generative models for end-to-end product requirements. Work closely with ML Researchers to define evaluation criteria and methodology to systematically evaluate foundation models. Conduct robust statistical analysis to identify model deficiencies and failure states. Minimum Qualifications
Master’s degree in Computer Science or other STEM majors 2+ years of hands-on industry experience with product focused statistical analysis for generative models Proficiency in Python and ML frameworks (Pytorch or Tensorflow) Preferred Qualifications
PhD in Computer Science, Machine Learning, Statistics or a related technical field 5+ years of hands-on industry experience with product focused statistical analysis for generative models Experience with experimental design, A/B testing and Failure Analysis Proficiency in training and evaluation of foundation models and frameworks A track record of publications or technical presentations in Machine Learning journals or conferences Excellent at communication and cross functional collaboration 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 $181,100 and $318,400, and your base pay will depend on your skills, qualifications, experience, and location.
The full job description covers all associated skills, previous experience, and any qualifications that applicants are expected to have.
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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Design and implement processes for evaluating multi-modal generative models for end-to-end product requirements. Work closely with ML Researchers to define evaluation criteria and methodology to systematically evaluate foundation models. Conduct robust statistical analysis to identify model deficiencies and failure states. Minimum Qualifications
Master’s degree in Computer Science or other STEM majors 2+ years of hands-on industry experience with product focused statistical analysis for generative models Proficiency in Python and ML frameworks (Pytorch or Tensorflow) Preferred Qualifications
PhD in Computer Science, Machine Learning, Statistics or a related technical field 5+ years of hands-on industry experience with product focused statistical analysis for generative models Experience with experimental design, A/B testing and Failure Analysis Proficiency in training and evaluation of foundation models and frameworks A track record of publications or technical presentations in Machine Learning journals or conferences Excellent at communication and cross functional collaboration 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 $181,100 and $318,400, and your base pay will depend on your skills, qualifications, experience, and location.
The full job description covers all associated skills, previous experience, and any qualifications that applicants are expected to have.
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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