Remote GenAI Data Scientist: LLM & RAG Expert

Fractal; United States; Remote; USD 150,000 - 180,000; Full time

Benefits offered by this job

Health insurance

401(k) plan

Remote work

Job summary

Fractal Analytics is seeking a Data Scientist – Generative AI with 8–10 years of experience to design, develop, and deploy AI/ML solutions with a strong focus on large language models and GenAI applications. You will collaborate with business, product, and engineering teams to deliver scalable, production-grade AI solutions.

This full-time remote role offers a competitive pay range and comprehensive benefits, emphasizing responsible AI, NLP, and scalable ML pipelines across cloud platforms.

Qualifications

• 8–10 years of Data Science/ML experience required.
• Proficient in Python (NumPy, Pandas, Scikit-Learn).
• Hands-on Generative AI and LLM experience; strong NLP foundation.

Responsibilities

• Design, develop, and deploy GenAI/LLM models for real-world use cases.
• Build and optimize RAG pipelines and agents.
• Process structured and unstructured data (text, logs, images).
• Develop end-to-end ML pipelines: data ingestion, Feature Engineering, training, validation, deployment.
• Collaborate with MLOps and engineering for monitoring, versioning, and scale.
• Communicate model outcomes to technical and non-technical stakeholders.

Skills

Python programming

Generative AI

LLMs

NLP concepts

LangChain/LlamaIndex

Cloud platforms

MLOps practices

SQL

Model evaluation

Communication to stakeholders

Education

Bachelor’s or Master’s in CS/DS/AI

Tools

LangChain

LlamaIndex

Docker/Kubernetes

MLflow

Job description

Fractal Analytics is seeking a Data Scientist – Generative AI with 8–10 years of experience to design, develop, and deploy AI/ML solutions with a strong focus on large language models and GenAI applications. You will collaborate with business, product, and engineering teams to deliver scalable, production-grade AI solutions.

This full-time remote role offers a competitive pay range and comprehensive benefits, emphasizing responsible AI, NLP, and scalable ML pipelines across cloud platforms.