Description

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

This role is remote.

Responsibilities

• Develop efficient, well-documented Python code for training, inference, and evaluation pipelines.
• Build RAG applications using embeddings, vector databases, and prompt engineering techniques.
• Integrate LLM applications into services and APIs, ensuring performance, reliability, and scalability.
• Establish model evaluation, monitoring, and governance practices covering quality, safety, bias, and drift.
• Collaborate with data engineering and platform teams on data pipelines, deployments, and CI/CD workflows.

Required Skills

• 6+ years of overall software development experience with a focus on AI/ML engineering.
• 2+ years of hands-on experience with deep learning for NLP or GenAI.
• Strong Python proficiency, including writing production-quality, testable, and maintainable code.
• Experience with deep learning frameworks (PyTorch or TensorFlow) and Hugging Face Transformers.
• Solid understanding of deep learning architectures, tokenization, attention mechanisms, and fine-tuning approaches.
• Experience building rapid prototypes and APIs using FastAPI, Flask, or Streamlit.
• Familiarity with MLOps practices including Docker, Kubernetes, CI/CD, and MLflow.

Preferred Skills

• Experience with LLM orchestration frameworks (LangChain, LlamaIndex, or similar) and vector databases.
• Experience deploying and scaling ML/LLM workloads on cloud platforms (Azure, GCP, or AWS).
• Familiarity with agentic architectures, multi-agent patterns, or healthcare domain knowledge.

Key Skills

Education

Bachelor's degree