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    Job · 19534965

    Apple logo

    PhD Intern, Machine Learning: MSI, Product Operations Team

    Apple · Bengaluru · onsite · Posted 23d ago

    Not disclosedFresherfulltimeSourced fromFoundit

    About a minute. You'll make an account on the way through.

    About this role

    Summary
    Imagine what you could do here. At Apple, new ideas have a way of becoming phenomenal products, services, and customer experiences very quickly. Every single day, people do amazing things at Apple. This position involves a wide variety of skills, innovation, and is a rare opportunity to be working on groundbreaking, new applications of machine learning, research, and implementation. Ultimately, your work would have a huge impact on billions of users across the globe. You can help inspire change, by using your skills to influence globally recognized products manufacturing.

    Description
    The goal of Apple's Manufacturing and Operations team is to take a vision of a product and turn it into a reality. Through the use of statistics, the scientific process, and machine learning, the team recommends and implements solutions to the most challenging problems. We're looking for ML researchers to help us revolutionize how we manufacture Apple's amazing products. Put your skill & passion to work in this highly visible role.

    Responsibilities
    • Research, build & adapt ML approaches for domain adaptation of multimodal foundation models to Apple manufacturing. Domain adaptation here is broad — spanning modalities including text, images, and video, such as generating physics-consistent videos adapted to Apple manufacturing
    • Develop techniques that steer large foundation models without modifying their weights, and multimodal knowledge-graph reasoning — domain-specific Q&A, multi-hop reasoning, disambiguation, and tool/retrieval orchestration over manufacturing knowledge
    • Train, evaluate, and analyze model performance (e.g., exact-match/F1 accuracy, explanation quality, and generation fidelity) on public benchmarks and on internal datasets where applicable
    • Apply and extend LLMs, VLMs, and World Models to advance domain adaptation for manufacturing
    • Collaborate within Apple to apply solutions to industrial problems
    • Conduct presentations of analyses and results to a wide range of audiences including executives

    Minimum Qualifications
    • Pursuing PhD in Computer Science / related field
    • Deep understanding of Machine Learning concepts, Probability and Statistics
    • Understanding of Computer Vision & VLMs, with demonstrated skill in training models and applying them to ML application development.
    • Ability to prototype research ideas as working code (Python)
    • Ability to meaningfully present results of analysis in a clear and impactful manner

    Preferred Qualifications
    • Familiarity with applying Machine Learning, especially Computer Vision in a Manufacturing / Assembly setting
    • Familiarity with multimodal understanding & reasoning, knowledge-graphs & generative video models
    • Prior publications in relevant field

    At Apple, we believe accessibility is a fundamental human right. You'll find that idea reflected in everything here — in our culture, our benefits and our digital tools. By welcoming as many perspectives as possible, we help you build a career where you feel like you belong.

    Learn about accessibility in Apple's workplace

    Role Number: [phone removed]

    Sourced from foundit

    Skills

    multimodal knowledge-graph reasoningprobabilityComputer VisionstatisticsLarge Language Models (LLMs)World ModelsVLMsPythonMachine Learning

    About Apple

    Apple logo

    Apple

    Consumer Electronics & Appliances

    12.3k+

    employees

    1976

    50 years old

    Cupertino, California

    United States (USA)

    About

    Apple focuses on innovative technology products and practices, enhancing user experiences while promoting sustainability and positive impact on society.

    Industries

    Consumer Electronics & AppliancesInternet

    Employee ratings

    706 reviews

    4.3/ 5

    Culture

    4.2

    Career growth

    3.7

    Work-life

    4.1

    Employees rate it well for

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