Pinterest

PhD Fall Machine Learning Intern (ATG: Visual, Multimodal, and Recommender Systems)

Stellenbeschreibung:

About Pinterest: Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime.

At Pinterest, we’re on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product.

Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other’s unique experiences and embrace the flexibility to do your best work.

Creating a career you love? It’s Possible.

At Pinterest, AI isn’t just a feature, it’s a powerful partner that augments our creativity and amplifies our impact, and we’re looking for candidates who are excited to be a part of that.

To get a complete picture of your experience and abilities, we’ll explore your foundational skills and how you collaborate with AI. Through our interview process, what matters most is that you can always explain your approach, showing us not just what you know, but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process here.

As a machine learning intern in our Advanced Technology Group at Pinterest, you will be exposed to a full spectrum of ML product development. The team focuses on developing cutting‑edge technologies for Pinterest’s visual understanding modules and recommender systems.

We offer a 12‑week fall internship program remotely or in our San Francisco, Palo Alto, Seattle, or New York offices.

Internships are 12 weeks paid from September21–December11,2026. Depending on the team, our fall internships will be located either remote or hybrid in SanFrancisco, Palo Alto, NewYork or Seattle offices.

Noteto applicants: By applying to this role, you will be considered for multiple intern roles open across our various ML teams. Please only apply once within the USA or Canada as multiple applications may delay our recruitment process.

What you’ll do

  • Develop and launch new user features using unique internal datasets and ML techniques, especially in recommendation systems, computer vision, representation learning, generative AI, and responsible AI.
  • Gain hands‑on experience with production ML systems, including algorithmic research, infrastructure, data engineering, training, inference, and product, to deliver innovative solutions.
  • Be exposed to full‑stack production ML systems.
  • Leverage frontier AI tools and agents to accelerate engineering implementation, including prototyping and experimentation work.
  • Validate AI‑generated outputs through testing, code review, and critical thinking, ensuring solutions are accurate, maintainable, secure, and aligned with team standards.
  • Use AI to better understand unfamiliar code, investigate bugs, and summarize technical context or documentation.
  • Contribute to cutting‑edge research in machine learning and artificial intelligence that can be applied to Pinterest problems.
  • Write clean, efficient, and sustainable code.
  • Take proactive ownership over the completion and quality of your tasks and projects with minimal guidance from your mentor, manager, and peers.

What we’re looking for

  • Visual Search or Applied Science teams.
  • Experience in Computer Vision, Visual Search, User Understanding, Recommendation Systems, Reinforcement Learning, ML efficiency optimization, Generative AI, and LLMs.
  • Ability to legally work full time (40 hours per week) from September–December2026.
  • Working towards a PhD degree in Computer Science, ML, NLP, Statistics, Information Sciences or related field.
  • Mastery of at least one systems language (Java, C++, Python) and one ML framework (Tensorflow, Pytorch, MLFlow).

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Stelleninformationen

  • Veröffentlichungsdatum:

    15 Jul 2026
  • Standort:

    Remote
  • Typ:

    Vollzeit
  • Arbeitsmodell:

    Vor Ort
  • Kategorie:

  • Erfahrung:

    2+ years
  • Arbeitsverhältnis:

    Angestellt

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