Machine Learning Data Scientist

Apple • Sunnyvale, CA

235d

About The Position

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.

Requirements

• BS in a quantitative field 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.

Nice To Haves

• 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.

Responsibilities

• 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.

What This Job Offers

• Career Level: Mid Level
• Education Level: Bachelor's degree
• Number of Employees: 5,001-10,000 employees