Description

You will build and deploy end-to-end ML solutions, applying GenAI and LLM concepts like RAG and embeddings to solve business problems.

This role is on-site.

Responsibilities

• Develop and maintain Python-based ML models using scikit-learn, PyTorch, and TensorFlow.
• Implement GenAI features including prompt engineering, embeddings, and RAG architectures.
• Own the full ML lifecycle from data processing to model deployment in cloud environments.
• Collaborate with technical and non-technical stakeholders to define requirements and deliver solutions.
• Utilize Azure ML and Databricks for scalable AI infrastructure and workflows.

Required Skills

• 4–7 years of experience in AI/ML engineering or applied data science.
• Strong proficiency in Python and core ML libraries (scikit-learn, PyTorch, TensorFlow).
• Practical experience with GenAI, LLMs, APIs, and embedding techniques.
• Hands-on experience deploying models in cloud environments, preferably Azure.
• Ability to communicate complex technical concepts to diverse audiences.

Preferred Skills

• Experience in healthcare, insurance, or regulated industries.
• Familiarity with Azure ML, Databricks, or agent-based AI systems.
• Consulting or client-facing delivery experience.

Key Skills

Education

Bachelor's degree