AI Engineer SLM Foundry (Small Language Models)

Merican Inc
Charlotte, NC, United States
2 months ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
5 years minimum
Working hours
Regular working hours
Job source

Tech stack

Artificial Intelligence Automated Storage and Retrieval Systems Program Optimization Computer Programming Python (Programming Language) Machine Learning Language Modeling Cloud Services Search Technologies Software Deployment Software Engineering Enterprise Software Applications
+8 more
Chatbots Large Language Models Multi-Agent Systems Prompt Engineering Generative AI AI Platforms HuggingFace Machine Learning Operations

Job description

We are looking for a talented AI Engineer with hands-on experience in Small Language Models (SLMs), Large Language Models (LLMs), and enterprise AI solutions to join our team., * Design, build, and optimize Small Language Models (SLMs) for enterprise use cases.

  • Develop and deploy AI/ML solutions using Python and modern AI frameworks.
  • Build Retrieval-Augmented Generation (RAG) pipelines, vector search, and retrieval systems.
  • Fine-tune, evaluate, and optimize transformer-based models.
  • Integrate LLM/SLM solutions into enterprise applications.
  • Work with MLOps, CI/CD pipelines, and cloud-based AI deployments.
  • Collaborate with product, engineering, and business stakeholders to deliver scalable AI solutions.

Requirements

  • 4 5 years of software engineering or AI engineering experience.
  • Strong programming expertise in Python.
  • Hands-on experience with SLM/LLM ecosystems and generative AI solutions.
  • Experience with LangChain, Hugging Face, LlamaIndex, RAG, or similar AI frameworks.
  • Strong understanding of AWS cloud services and AI deployment architectures.
  • Experience deploying AI models into production environments.
  • Knowledge of vector databases, embeddings, and semantic search technologies.

Preferred Qualifications:

  • Experience with enterprise AI platforms.
  • Knowledge of model optimization, inference tuning, and performance improvements.
  • Exposure to financial services or regulated industry environments.
  • Experience with prompt engineering, multi-agent systems, or conversational AI is a plus.

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