Data Scientist

Talantir; Raleigh (NC); On-site; USD 120,000 - 180,000; Full time

Job summary

Talantir is seeking a hands-on Data Scientist to lead the development and deployment of next-generation AI solutions leveraging LLMs, RAG, and agentic frameworks. You will prototype, train, and productionize models, collaborating with product and engineering teams.

Ideal candidates have strongPython, experience with Hugging Face libraries, vector databases, and cloud services. You will implement LLMOps, evaluate models, and ensure scalable, governance-backed AI systems in a fast-moving

Qualifications

• Experience in Gen AI or LLM-based systems.
• Strong Python programming skills and ML/AI libraries (e.g., PyTorch, Transformers).
• Hands-on experience with vector databases (FAISS, Pinecone, Weaviate, Azure AI Search).
• Familiarity with cloud platforms and Gen AI services (AWS, Azure, GCP).
• Experience with REST API development (FastAPI, Flask) and containerization (Docker).
• Solid understanding of AI governance, model safety, and prompt engineering.

Responsibilities

• Design, develop, and deploy Gen AI applications using LLMs and agentic frameworks.
• Fine-tune open-source and proprietary LLMs using techniques like LoRA, QLoRA, and PEFT.
• Build and optimize RAG pipelines with hybrid retrieval, semantic chunking, and vector search.
• Integrate Gen AI solutions with cloud-native services (AWS Bedrock, Azure OpenAI, GCP Vertex AI).
• Work with unstructured data (PDFs, HTML, audio, images) and multimodal models.
• Implement LLMOps practices including prompt versioning, caching, observability, and cost tracking.
• Evaluate model performance using tools like RAGAS, DeepEval, and FMeval.
• Collaborate with product managers, data engineers, and UX teams to deliver production-ready solutions.

Skills

Python programming

Gen AI/LLM-based systems

Prompt engineering

REST API development

Containerization

Tools

Hugging Face Transformers

LangChain

PyTorch

FAISS

Pinecone

Weaviate

Azure AI Search

AWS Bedrock

Azure OpenAI

GCP Vertex AI

FastAPI

Flask

Docker

Job description

Client is seeking a hands-on Data Scientist to drive the development and deployment of next-generation AI solutions using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and Agentic AI frameworks.

Required Qualifications

• Experience in software engineering or data science, with in Gen AI or LLM-based systems.
• Strong Python programming skills and experience with ML/AI libraries (Hugging Face Transformers, LangChain, PyTorch).
• Hands-on experience with vector databases (FAISS, Pinecone, Weaviate, Azure AI Search).
• Familiarity with cloud platforms and Gen AI services (AWS, Azure, GCP).
• Experience with REST API development (FastAPI, Flask) and containerization (Docker).
• Solid understanding of AI governance, model safety, and prompt engineering.

Key Responsibilities

• Design, develop, and deploy Gen AI applications using LLMs and agentic frameworks (e.g., LangGraph, AutoGen, Crew AI).
• Fine-tune open-source and proprietary LLMs using techniques like LoRA, QLoRA, and PEFT.
• Build and optimize RAG pipelines with hybrid retrieval, semantic chunking, and vector search.
• Integrate Gen AI solutions with cloud-native services (AWS Bedrock, Azure OpenAI, GCP Vertex AI).
• Work with unstructured data (PDFs, HTML, audio, images) and multimodal models.
• Implement LLMOps practices including prompt versioning, caching, observability, and cost tracking.
• Evaluate model performance using tools like RAGAS, DeepEval, and FMeval.
• Collaborate with product managers, data engineers, and UX teams to deliver production-ready solutions.