AI and Machine Learning Internship

3 weeks ago

Nagpur, India FinSocial Digital systems Full time
Company: FinSocial Digital Systems
Location: Remote
Duration: 4 months
Type: Unpaid Internship
Hours: Full-time, Monday to Friday, 9 AM to 5 PM
About Us:
FinSocial Digital Systems is an innovative platform revolutionizing finance through AI-driven solutions across various sectors, including traditional and digital assets. Join our team as we build the next generation of AI-powered tools for the financial world.
Position Summary:
We are looking for a passionate AI and Machine Learning Intern proficient in Python and familiar with open-source large language models (LLMs) to assist in developing, fine-tuning, and deploying cutting-edge models for our platform. This is an unpaid, full-time internship that will run from 9 AM to 5 PM, Monday to Friday . Please note: Students will not be preferred for this position, as full-time availability is required. If you are unable to commit to these hours, please do not apply.
Responsibilities:
Assist in developing, fine-tuning, and deploying large language models (LLMs) using open-source models like Mistral, LLaMA, Bloom, etc.
Work with the Hugging Face ecosystem to experiment with and optimize model performance.
Build interactive web applications using Streamlit to demonstrate model outputs and streamline user interactions.
Use LangChain to build complex chains and pipelines for large language model applications.
Collaborate with the team to integrate AI models into existing pipelines and explore new applications within the financial domain.
Contribute to documentation and reports, showcasing your learning and results.
Required Skills and Qualifications:
Proficiency in Python: Demonstrable experience with Python, including popular libraries used in machine learning.
Familiarity with Open-Source LLMs: Experience working with models like Mistral, LLaMA, Bloom, etc.
Proficiency with Hugging Face: Able to navigate and leverage Hugging Face’s libraries, such as Transformers and Datasets, to work with pre-trained models.
Streamlit and Ollama Experience: Skilled in using Streamlit for web app development and familiar with Ollama for model management.
Familiarity with LangChain: Experience in creating workflows, chains, and pipelines for language models.
Analytical Mindset: Strong analytical skills, with the ability to dissect problems, think critically, and apply learned techniques.
Preferred Skills:
Prior exposure to deep learning frameworks such as TensorFlow or PyTorch.
Familiarity with additional LLM deployment tools and platforms.
Experience with prompt engineering for LLMs and understanding fine-tuning techniques.
What You'll Gain:
Hands-on experience with state-of-the-art open-source LLMs and ML deployment.
Exposure to real-world applications of AI in finance and fintech.
Mentorship from seasoned professionals and the chance to work in a collaborative, innovative environment.
A strong foundation in deploying machine learning applications, a valuable addition to your portfolio.

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