Key Responsibilities
Model Development:
Design, build, train, and optimize machine learning and deep learning models for real-world applications.
Cross-Functional Collaboration:
Work closely with product managers, data scientists, and software engineers to define AI/ML use cases and deliver high-impact solutions.
LLM Fine-Tuning:
Evaluate and fine-tune pre-trained Large Language Models (LLMs) for domain-specific tasks and performance improvements.
Model Deployment:
Deploy models into production using APIs, Docker containers, and cloud platforms such as AWS, GCP, or Azure.
Research & Innovation:
Stay updated with the latest AI/ML advancements, tools, and best practices to drive continuous innovation within the team.
Preferred Qualifications
Bachelor's or Master's degree in Computer Science, Data Science, AI, or a related field.
Strong experience with machine learning frameworks (TensorFlow, PyTorch, scikit-learn).
Proficiency in Python and relevant libraries (NumPy, Pandas, Transformers, etc.).
Experience deploying models in cloud environments.
