GenAI & LLM Engineer for Production ML Systems

SFE; Woodlands (CA); Sur place; USD 140 000 - 210 000; Plein temps

Résumé du poste

SFE is seeking an hands-on AI/ML Engineer in Woodlands, CA to design, build, and deploy production-grade ML and GenAI solutions. You will leverage Python expertise to implement end-to-end pipelines, including prompt engineering for LLMs, document processing, and embedding-based search.

The role focuses on end-to-end ML workflows, integrating vector databases and MongoDB, and ensuring scalable, production-ready deployments with CI/CD and cloud platforms.

Qualifications

• Strong Python expertise with production-grade ML experience.
• Hands-on experience deploying GenAI/LLM use cases.
• Experience building document processing pipelines and vector search.
• Familiarity with vector databases and MongoDB integration.
• Ability to design scalable ML solutions from data to production.

Responsabilités

• Design, build, and deploy production-grade ML/GenAI solutions.
• Develop and optimize prompt engineering for LLM-based systems.
• Build Retrieval-Augmented Generation pipelines with vector search.
• Integrate LLMs via APIs into enterprise applications.
• Develop agentic AI workflows and tool calling capabilities.
• Implement CI/CD and cloud deployment with observability.
• Collaborate with data engineers, product owners, and platform teams.
• Stay updated on evolving ML/GenAI tech and apply to projects.

Connaissances

Python

ML training

GenAI & LLMs

Prompt engineering

Document processing

Embeddings

Vector search

Vector databases

MongoDB

Production ML engineering

Description du poste

SFE is seeking an hands-on AI/ML Engineer in Woodlands, CA to design, build, and deploy production-grade ML and GenAI solutions. You will leverage Python expertise to implement end-to-end pipelines, including prompt engineering for LLMs, document processing, and embedding-based search.

The role focuses on end-to-end ML workflows, integrating vector databases and MongoDB, and ensuring scalable, production-ready deployments with CI/CD and cloud platforms.