Artificial Intelligence Intern - Remote

0 years

0 Lacs

Posted:2 weeks ago| Platform: Foundit logo

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Work Mode

Remote

Job Type

Full Time

Job Description

About the Company:

learning and hiring

AI interns

Roles & Responsibilities:

  • Contribute to the development and fine-tuning of ML models using

    Python

    and

    PyTorch

    .
  • Experiment with modern LLMs and generative AI models

    to solve real product challenges.
  • Work with a variety of tools and frameworks like

    Transformers, LangChain, OpenAI API, LlamaIndex

    , and others for tasks such as classification, generation, and retrieval.
  • Help build and optimize training scripts, inference pipelines, and evaluation tools.
  • Conduct literature reviews or repo deep-dives to bring new ideas from the

    rapidly evolving AI ecosystem

    into production.
  • Assist in cleaning, preprocessing, and analyzing datasets.
  • Work closely with engineers and founders to prototype and test AI-powered features.

Skills & Qualifications:

  • Strong programming skills in

    Python

    .
  • Good understanding of

    machine learning fundamentals

    (loss functions, metrics, overfitting, etc.).
  • Some hands-on experience with

    deep learning libraries

    (e.g., PyTorch, TensorFlow).
  • Familiarity with

    modern NLP and generative AI tools

    such as Hugging Face Transformers, OpenAI, Claude, LLaMA, LangChain, or similar.
  • Awareness of ongoing trends in the AI/LLM space and eagerness to explore new tools and models.
  • Self-motivated and proactive mindset youre not afraid to explore, experiment, and learn on the go.
  • Bonus:

    Youve worked on AI/ML side projects, GitHub repos, Kaggle competitions, or open-source contributions.

Benefits:

  • Mentorship and

    direct collaboration with the founding team

    .
  • Real-world experience applying AI to product use cases.
  • Ownership of small but impactful features and experiments.
  • A fully

    remote and async-friendly

    work culture.
  • Opportunity for

    long-term collaboration

    based on performance.

Note:

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