Job Description
Roles & Responsibilities
- Design, develop, and implement AI/ML solutions based on business requirements.
- Build, train, evaluate, and deploy machine learning and deep learning models.
- Work with Large Language Models (LLMs) to fine-tune models, perform prompt engineering, and apply them to specific use cases.
- Experiment with and evaluate different LLM architectures to identify optimal solutions.
- Perform data analysis, data visualization, and statistical modeling to extract insights from data.
- Collaborate with cross-functional teams to integrate AI/ML models into production systems.
- Optimize model performance and ensure scalability and reliability of solutions.
- Use version control systems to manage code and collaborate effectively.
- Troubleshoot and solve complex technical problems related to AI/ML systems.
Required Skills:
- Strong programming skills in Python and experience with libraries such as TensorFlow, PyTorch, scikit-learn, Pandas, and NumPy.
- Solid understanding of machine learning algorithms, including supervised, unsupervised, and reinforcement learning.
- Hands-on experience with deep learning frameworks and architectures (CNNs, RNNs, Transformers).
- Experience working with Large Language Models (LLMs) such as GPT, BERT, or similar.
- Knowledge of fine-tuning LLMs, prompt engineering, and applying LLMs to real-world tasks.
- Understanding of the strengths and limitations of current LLM technologies.
- Strong background in data science, including data analysis, data visualization, and statistical modeling.
- Experience with SQL and NoSQL databases.
- Familiarity with cloud platforms such as AWS, Azure, or GCP and their AI services.
- Proficiency in version control tools like Git and GitHub.
- Excellent analytical, problem-solving, and debugging skills.