Do you have a passion for computer vision, large language models, 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, machine learning, and multi-modal LLM (MM-LLM) to join our dynamic team. The ideal candidate will be responsible for evaluating machine learning and MM-LLM models, developing performance metrics, and conducting thorough failure analysis. This role requires a deep understanding of ML algorithms, data processing, model optimization techniques, and modern evaluation approaches for vision-language models.
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.
Eeo Content
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.
