Description

You will design, build, and fine-tune NLP and LLM solutions for business use cases including classification, summarization, and Q&A.

This role is remote.

Responsibilities

• Design and implement NLP/LLM solutions for classification, summarization, and Q&A tasks.
• Build RAG applications using embeddings, vector databases, and prompt engineering techniques.
• Develop production-grade Python code for training, inference, and evaluation pipelines.
• Integrate LLM applications into services/APIs with a focus on performance and scalability.
• Establish model evaluation, monitoring, and governance practices for quality and safety.

Required Skills

• 6+ years of overall experience in software development, data analytics, data science, or ML engineering.
• 2+ years of hands-on experience with deep learning for NLP/GenAI.
• Strong Python proficiency, including writing production-quality, testable, and maintainable code.
• Experience with deep learning frameworks: PyTorch or TensorFlow; Hugging Face Transformers.
• Experience building rapid prototypes and APIs using FastAPI/Flask and/or Streamlit.
• Experience with MLOps: model packaging, CI/CD, Docker, Kubernetes, MLflow, and monitoring.
• Software engineering skills: Git, code reviews, unit/integration testing (pytest), REST APIs.

Preferred Skills

• Experience with LLM orchestration frameworks (LangChain, LlamaIndex, Semantic Kernel).
• Experience with vector databases and embedding workflows (FAISS, Pinecone, Weaviate, Chroma, Azure AI Search).
• Experience deploying and scaling ML/LLM workloads on cloud platforms (Azure preferred; GCP/AWS acceptable).

Key Skills

Education

Bachelor's degree