AI and Machine Learning Internship
4 weeks ago
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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