Job Description
Do you have a passion for computer vision and deep learning? The Video Engineering Data Analytics and Quality (DAQ) group is looking for an experienced Data Scientist with a strong background in computer vision and machine learning to join our dynamic team. The ideal candidate will be responsible for evaluating machine learning models, developing performance metrics, and conducting thorough failure analysis. This role requires a deep understanding of machine learning algorithms, data processing, and model optimization techniques.
Description
Evaluate Machine Learning Models: Analyze and validate machine learning and computer vision models to ensure they meet performance standards.
Develop Metrics: Design and implement metrics to measure the effectiveness and accuracy of models.
Failure Analysis: Perform detailed failure analysis to understand model weaknesses and identify areas for improvement.
Data Processing: Preprocess and clean large datasets to prepare them for modeling.
Model Optimization: Optimize models for performance and scalability, applying state-of-the-art techniques.
Collaborate: Work closely with cross-functional teams, including software engineers, product managers, and other data scientists, to integrate models into production.
Documentation: Document processes, model performance, and analysis results.
Minimum Qualifications
- BS and a minimum of 4 years relevant industry experience.
- Solid 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
Key Qualifications
Preferred Qualifications
- Experience crafting, conducting, analyzing, and interpreting experiments and investigations
- Proven expertise in data wrangling and developing data visualizations & reporting with toolings such as Tableau, Superset, AWS etc.
- Detail-oriented to keep track of and understand the workings of complex algorithms
- Self-motivated and curious with creative and critical thinking capabilities to improve data quality evaluation methods for diverse and complex data annotation programs
- Outstanding verbal and written communication skills, along with strong collaborative abilities
- Experience presenting data to stakeholders
- Familiar with machine learning interpretability methods is a big plus
- Familiarity with various foundation models, such as SAM, LLAMA, LLaVA, CGPT4V, CLIP is nice to have
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 $132,300 and $241,500, 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 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.
Evaluate Machine Learning Models: Analyze and validate machine learning and computer vision models to ensure they meet performance standards.
Develop Metrics: Design and implement metrics to measure the effectiveness and accuracy of models.
Failure Analysis: Perform detailed failure analysis to understand model weaknesses and identify areas for improvement.
Data Processing: Preprocess and clean large datasets to prepare them for modeling.
Model Optimization: Optimize models for performance and scalability, applying state-of-the-art techniques.
Collaborate: Work closely with cross-functional teams, including software engineers, product managers, and other data scientists, to integrate models into production.
Documentation: Document processes, model performance, and analysis results.
Job Tags
Relocation,