Machine Learning Engineer

Key Responsibilities Design, build, and deploy

production-grade AI/ML solutions

end-to-end. Develop

scalable ML and Generative AI applications

using Python and SQL. Build and fine-tune ML models using libraries such as

Scikit-learn, XGBoost, and LightGBM . Work on

NLP/GenAI initiatives

leveraging frameworks like

Hugging Face, LangChain, and LlamaIndex . Implement and integrate

vector database–based solutions

for search, retrieval, and

RAG pipelines . Develop and deploy

ML/GenAI services using FastAPI or Flask . Containerize and deploy applications using

Docker and Kubernetes . Work with

cloud-native ML platforms

such as

AWS (SageMaker), GCP (Vertex AI), or Azure ML . Utilize and integrate

Text-to-SQL models such as SQLCoder . Required Skills Strong proficiency in

Python and SQL . Solid understanding of

machine learning algorithms and the model lifecycle . Experience with

Generative AI, LLMs, embeddings, vector databases, and RAG architectures . Hands-on experience developing

APIs and deploying ML services . Cloud experience with at least one major provider ( AWS, GCP, or Azure ).