AI Engineer: LLMs, GenAI & Cloud Architect

Machine Learning Technologies, LLC

Jersey City (NJ)

On-site

USD 120,000 - 180,000

Full time

2 hours ago
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Job summary

Machine Learning Technologies, LLC is seeking an AI Engineer to conduct research on AI/ML technologies and architectures, deploy AI/LLM and agentic applications for PoC demonstrations, and assist in scaling solutions for production. You will explore Gen AI and Agentic AI, staying abreast of AI trends and evaluating third-party solutions.

Collaborating with AI Business Partners, you will contribute to data preparation, synthetic data strategies, and ensure model performance and safety across

Qualifications

  • Experience in AI/ML systems design and deployment.
  • Proficiency with Python, APIs, ML frameworks and AI tooling.
  • Familiarity with cloud services (AWS/GCP) and data handling.

Responsibilities

  • Conduct R&D on AI/ML technologies and architectures.
  • Deploy AI/LLM and agentic applications for PoC and production scaling.
  • Explore traditional AI, Gen AI and Agentic AI approaches.
  • Stay current on AI trends and evangelize emerging technologies.
  • Evaluate third-party AI solutions for scalability and business value.
  • Prototype solutions to inform future productization.
  • Collaborate on data preparation and synthetic data strategies.
  • Validate model performance, safety, and readiness.
  • Contribute to AI system architecture and cloud workflows.
  • Collaborate with AI Business Partners.

Skills

Python
APIs
ML frameworks
AI tools
GitHub Copilot
Codex
Claude
LangChain
Vector databases
AWS
GCP

Tools

AWS
GCP

Job description

Machine Learning Technologies, LLC is seeking an AI Engineer to conduct research on AI/ML technologies and architectures, deploy AI/LLM and agentic applications for PoC demonstrations, and assist in scaling solutions for production. You will explore Gen AI and Agentic AI, staying abreast of AI trends and evaluating third-party solutions.

Collaborating with AI Business Partners, you will contribute to data preparation, synthetic data strategies, and ensure model performance and safety across

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