Machine Learning Engineer

6 days ago


Bengaluru India Capgemini Full time

Job Description 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.



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