Data Scientist

2-5 Years

Engineering

Remote

Engineering

Remote

We are looking for an AI/ML Engineer with expertise in NLP, Generative AI, and Language Models (LLMs), particularly in Retrieval-Augmented Generation (RAG). The ideal candidate should be proficient in Python and experienced with FastAPI and Streamlit for building user-friendly applications and rapid prototyping. The role involves collaborating on AI model development, conducting evaluations to improve performance, and delivering Proofs of Concept (POCs). You will work closely with cross-functional teams to integrate and deploy AI solutions, while also staying updated on emerging frameworks. Strong communication skills and the ability to manage project delivery are key. Experience with agentic frameworks and basic machine learning concepts is a plus.

Responsibilities:

Collaborate in developing and enhancing NLP, RAG, and LLM-related projects and ensuring their effectiveness and robustness.

Proactive in gathering and understanding data and requirements for the projects.

Conduct model evaluations using established metrics and provide insights for model improvement.

Rapidly build Proof of Concepts (POCs) by working closely with internal and external stakeholders.

Confident is using FastAPI and Streamlit to create effective, user-friendly interfaces and endpoints as needed.

Coordinate with Product managers, DevOps and other team members to manage integrations and ensure successful testing.

Actively research and adopt emerging frameworks and methodologies to enhance our applications.

Exhibit strong communication skills, ensuring clear updates and feedback loops with all stakeholders.

Key Skills and Expertise Required:

Programming & Frameworks: Proficient in Python, with experience in FastAPI and Streamlit for rapid prototyping.

NLP & Generative AI: Strong foundation in NLP, Generative AI, Language Models (LLMs), and Retrieval-Augmented Generation (RAG).

Model Development & Evaluation: Capable of building and evaluating AI and ML models and evaluate with metrics to assess model performance.

Agentic Frameworks: Familiarity with agentic frameworks (e.g., LangGraph or alternatives) is preferred. (good to have)

Basic Machine Learning and Deep Learning: Sound knowledge of foundational ML and DL concepts.

Project Delivery & Coordination: Demonstrated ability to collaborate with DevOps and other stakeholders for smooth integration, testing, and deployment of AI applications.