Machine Learning Data Scientist

Apple-posted 2 months ago
Sunnyvale, CA
5,001-10,000 employees
Computer and Electronic Product Manufacturing
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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. 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.

  • 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.
  • 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.
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