Description

You will design and implement machine learning models and production-grade AI applications.

Responsibilities

• Build and optimize Retrieval Augmented Generation (RAG) systems and prompt engineering workflows.
• Manage the full data lifecycle including synthetic data generation, cleaning, preprocessing, and exploratory data analysis.
• Develop and maintain ML pipelines featuring tokenization, embedding models, and unit testing.
• Implement data validation, drift detection, and LLM output evaluation to mitigate hallucinations.
• Deploy scalable models using Docker and cloud environments.

Required Skills

• 5+ years of software development experience.
• Proficiency in Python, Java, Spring Boot, and FastAPI.
• Experience with PyTorch and TensorFlow/Keras.
• Hands-on work with LangChain and NLP libraries like NLTK or spaCy.
• Practical application of vector databases such as ChromaDB, FAISS, or pgvector.
• Data manipulation skills using pandas and Matplotlib.
• Database management with PostgreSQL and NoSQL.
• Frontend experience with ReactJS or Svelte.
• Knowledge of cloud deployment on AWS, GCP, or Azure.
• Familiarity with Docker, Git, and Agile methodologies.
• Bachelor’s or Master’s degree in Computer Science, Computer Engineering, or a related technical discipline.

Key Skills

Education

Any Graduate