Artificial Intelligence Engineer

Key Responsibilities

Model Development & Training :

Develop, train, and optimize ML and generative AI models including LLMs, transformers, diffusion models, and embedding-based models.

Generative AI Applications :

Build real-world generative AI applications such as chatbots, RAG systems, summarization, content generation, and agent frameworks.

Prompt Engineering & LLM Integration :

Apply prompt design, tuning, and evaluation techniques using tools like LangChain, LlamaIndex, or similar frameworks.

Data Pipeline & MLOps :

Build scalable ML pipelines for data ingestion, feature engineering, model deployment, and monitoring using MLOps best practices.

Cloud & Infrastructure :

Deploy models and services on AWS / GCP / Azure, leveraging containerization (Docker / Kubernetes) and GPU infrastructure.

Research & Innovation :

Stay current with AI research, experiment with new models, and contribute ideas for enhancements and automation.

Documentation & Collaboration :

Maintain clear technical documentation and collaborate with cross-functional engineering and product teams.

Required Skills & Experience

2+ years of experience in Machine Learning / AI engineering roles

Hands-on experience with Generative AI / LLMs / Transformers

Strong programming skills in Python and frameworks like PyTorch / TensorFlow

Experience with vector databases (Pinecone, ChromaDB, Weaviate, FAISS)

Solid understanding of LangChain, LlamaIndex, RAG, embeddings, prompt tuning

Familiarity with cloud deployment (AWS / GCP / Azure) and CI / CD pipelines

Strong analytical problem-solving skills and knowledge of ML lifecycle

Excellent communication and teamwork abilities