Job Title

Basic understanding of machine learning frameworks such as TensorFlow, PyTorch, or Hugging Face. • Knowledge of neural network architectures, particularly in areas like Transformers and basic deep learning models. • Familiarity with Python programming and essential ML libraries (NumPy, Pandas, Scikit-learn). • Exposure to NLP (Natural Language Processing) concepts and basic text processing tasks. • Some experience with cloud platforms (AWS, GCP, or Azure) for deploying simple AI models. • Understanding of basic databases and their integration with AI systems (NoSQL or SQL databases). Soft Skills: • Strong eagerness to learn and adapt to new technologies in the AI and machine learning field. • Ability to work under guidance and collaborate within a team environment. • Good problem-solving abilities and analytical thinking. • Effective communication skills to discuss technical issues and progress with the team. Education and Experience: • Bachelor’s degree in computer science, Data Science, Artificial Intelligence, or related fields. • 6-9 years of experience in machine learning, AI, or related areas (internships or academic projects are a plus). Preferred Skills (Nice-to-Have): • Exposure to basic machine learning deployment tools or practices. • Familiarity with any vector databases (ChromaDB, Pinecone, Weaviate, Milvus, FAISS) or graph databases (Neo4j, TigerGraph). • Interest in generative AI or graph-based AI solutions. • Involvement in open-source projects or personal contributions to machine learning communities. • Understanding of ethical AI principles or data privacy basics. Role Summary: As a Junior Machine Learning Developer, you will be part of a dynamic team working on cutting-edge AI and machine learning solutions. This role offers an exciting opportunity for a motivated individual to learn and grow their skills in a fast-paced, collaborative environment. You will assist senior developers in developing, testing, and deploying AI models, while gaining hands-on experience with machine learning frameworks and real-world AI applications.