About the role:

• 
  
We are seeking a motivated Machine Learning Intern to join our ML Engineering team. In this role, you will actively contribute to:
• Optimizing and benchmarking state-of-the-art Large Language Models (LLMs)
• Evaluating and enhancing ML pipelines, encompassing data preprocessing, model training, and rigorous performance analysis
• Fine-tuning expert models to use in agentic AI workflows
• Leveraging cloud-based ML services (AWS/GCP) to deploy GenAI solutions into production environments
• Staying on top of the rapidly evolving GenAI landscape through continuous research

Requirements:

• Graduate student in Computer Science, Applied Mathematics, Physics, or other STEM field;
• Proficiency in Python (required);
• Proficiency in libraries for data analysis (e.g., Pandas, SciPy, NumPy);
• Familiarity with ML libraries (e.g., scikit-learn, PyTorch);
• Experience with version control using Git;
• An analytical mindset and the ability to learn quickly;
• Upper-Intermediate English (written/spoken).

Nice-to-Have:
• Coursework/projects in ML, data analysis, or automation;
• Familiarity with MLOps tools and practices for model training and evaluation (e.g., MLflow, Weights & Biases);
• Familiarity with LLM frameworks (e.g., llamaindex, Langchain, Hugging Face);
• Experience with Docker;
• Experience with cloud platforms (e.g., AWS).

What you get from the internship:

• Payment and a flexible hybrid working environment;
• Gain deep expertise in evaluating, benchmarking, and optimizing LLMs;
• Enhance your research, AWS/ GCP, Python programming, and data analysis skills;
• Learn best practices for deploying GenAI solutions in a production setting;
• Real-world project experience and receive a letter of recommendation to accelerate your career;
• Opportunity to contribute to publication;
• Mentorship and learning opportunities from experienced engineers.

Apply now to kickstart your ML career!