Description

Description

Our organization supports a diverse array of programs passionate about evaluating ML algorithms and assessing model quality at scale, across domains like computer vision, audio, and multi-modal systems. You will collaborate with multi-functional teams, including domain experts and engineering leads, and adapt methodologies as new insights emerge. In this role you will: - Evaluate ML & MM-LLM Models: Analyze and validate computer vision, multi-modal, and large language models to ensure they meet accuracy, robustness, and usability standards. - Develop Metrics: Design and implement metrics to measure the efficiency and accuracy of models. - Failure Analysis: Conduct in-depth analysis on model failures across CV and MM-LLM pipelines to surface root causes and improvement areas. - Data Processing: Clean, transform, and curate large-scale datasets for model evaluation and benchmarking. - Model Optimization: Apply innovative techniques to optimize models for scalability and real-world deployment. - Collaborate multi-functionally: Work closely with cross-functional teams, including software engineers, product managers, and other data scientists, to integrate models into production. - Communicate Results: Present findings clearly and effectively to collaborators across levels of technical understanding.

Minimum Qualifications

• BS and a minimum of 3 years relevant industry experience
• Proven background in data science, machine learning, computer vision and statistical data analysis.
• Advanced programming skills in data manipulation & processing (SQL & Python preferred).
• Demonstrated experience in in-depth analysis of machine learning model failures.
• Experience crafting, conducting, analyzing, and interpreting experiments and investigations.
• Expertise in data wrangling and developing data visualizations & reporting with toolings such as Tableau, Superset, AWS etc.

Preferred Qualifications

• Experience working with multi-modal foundation models such as GPT-4o, Gemini 2.5, Claudi 3/4, LLaVA, Flamingo, etc.
• Familiar with machine learning interpretability method and standard processes.
• Exposure to evaluating vision-language models in production or research settings.
• Experience handling complex programs and collaborating across engineering, product, and data teams.
• Detail-oriented to keep track of and understand the workings of sophisticated algorithms.
• Strong attention to detail in working with large datasets and complex ML systems.
• Curious, self-motivated, and able to drive improvements to model evaluation pipelines and annotation programs.
• Outstanding communication skills - both written and verbal - with experience presenting to leadership.

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 $147,400 and $272,100, 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 .