Machine Learning Engineer

4 weeks ago

Bengaluru, Karnataka, India Capgemini Full time

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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