Machine Learning Developer

•    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.
•    2-4 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.