Key Responsibilities
- Develop and refine machine learning models for talent matching, ranking, and semantic scoring using Python and AI/ML libraries
- Build scalable data pipelines to process structured and unstructured data from resumes and job descriptions
- Deploy models into production environments and monitor their performance in live client-facing systems
- Collaborate with cross-functional teams to design and implement end-to-end AI system architectures
- Conduct experiments with new algorithms and LLM-based components to enhance existing models
- Participate in code reviews, documentation, and continuous improvement processes to maintain high-quality standards
Requirements
- Final-year student or recent graduate in Computer Science, AI/ML, or a related field
- Strong programming skills in Python with hands-on experience using scikit-learn, Pandas, and NumPy
- Exposure to NLP, transformers, or LLMs through frameworks like Hugging Face or LangChain
- Understanding of building, evaluating, and deploying machine learning models
- Familiarity with Git and basic MLOps practices