Artificial Intelligence Engineer - Python

Description :

We are looking for a passionate and skilled AI Engineer to join our AI/ML team. The ideal candidate will have strong hands-on experience in Python, Machine Learning, Natural Language Processing (NLP), and Retrieval-Augmented Generation (RAG) techniques. You will work on designing, developing, and deploying intelligent models and AI-driven applications in real-world environments.

Responsibilities :

- Design, develop, and deploy AI and ML models to solve business and product challenges.

- Build and optimize NLP pipelines for tasks such as text classification, entity extraction, and sentiment analysis.

- Implement Retrieval-Augmented Generation (RAG) architectures using LLMs and vector databases.

- Fine-tune pre-trained Large Language Models (LLMs) for domain-specific applications.

- Develop and integrate AI solutions into production systems using Python APIs or web frameworks.

- Collaborate with data engineers, backend developers, and product teams to ensure scalable AI deployment.

- Research and experiment with emerging AI/ML tools, frameworks, and architectures to improve model performance.

- Evaluate and monitor AI model performance using key metrics (accuracy, F1-score, perplexity, etc.).

Requirements :

- 4-8 years of hands-on experience in AI/ML model development and deployment.

- Strong programming skills in Python and familiarity with machine learning frameworks like TensorFlow, PyTorch, or Hugging Face Transformers.

- Experience with Natural Language Processing (NLP) tokenization, embeddings, and transformer-based architectures (BERT, GPT, etc.).

- Practical knowledge of Retrieval-Augmented Generation (RAG) using tools like LangChain, LlamaIndex, or FAISS.

- Proficiency in vector databases (Pinecone, ChromaDB, Weaviate, Milvus, etc.).

- Strong understanding of data preprocessing, feature engineering, and model evaluation.

- Experience in cloud deployment (AWS, GCP, or Azure) and containerization (Docker).

- Experience working with LLM APIs (OpenAI, Anthropic, Mistral, etc.).

- Familiarity with knowledge graph construction or semantic search systems.

- Understanding of data pipelines and ETL workflows.

- Knowledge of API development or backend integration with Flask/FastAPI.