AI Engineer: GenAI & LLM Systems R&D to Deployment

MACHINE LEARNING TECHNOLOGIES LLC

Jersey City (NJ)

On-site

USD 120,000 - 190,000

Full time

46 hours ago
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Job summary

MACHINE LEARNING TECHNOLOGIES LLC in Jersey City, NJ seeks an AI Engineer to perform R&D on AI/ML technologies and architectures. You will deploy AI/LLM solutions for proofs-of-concept and help scale them for production, exploring Gen AI and agentic AI approaches while staying abreast of emerging trends and evaluating third-party AI solutions.

The role involves prototyping, data preparation, synthetic data strategies, and validating model performance and safety in cloud environments.

Qualifications

  • Proficiency in Python for AI/ML development.
  • Experience with APIs, ML frameworks and AI tooling.
  • Familiarity with LLMs, embeddings, and AI architectures.

Responsibilities

  • Conduct R&D on AI/ML technologies and architectures.
  • Deploy AI/LLM and agentic applications for proofs-of-concept; assist scaling.
  • Explore traditional AI, Gen AI, and Agentic AI implementations.
  • Stay current on AI trends and evangelize emerging tech.
  • Evaluate and pilot third-party AI solutions for value.
  • Prototype solutions to inform future productization.
  • Collaborate on data prep and synthetic data generation strategies.
  • Validate model performance, safety, and operability.
  • Contribute to AI system architecture and cloud workflows.
  • Collaborate with AI Business Partners.

Skills

Python
APIs
ML frameworks
AI tools

Tools

GitHub Copilot
Codex
Claude
Lang Chain
ADK
Chat GPT
MS Copilot

Job description

MACHINE LEARNING TECHNOLOGIES LLC in Jersey City, NJ seeks an AI Engineer to perform R&D on AI/ML technologies and architectures. You will deploy AI/LLM solutions for proofs-of-concept and help scale them for production, exploring Gen AI and agentic AI approaches while staying abreast of emerging trends and evaluating third-party AI solutions.

The role involves prototyping, data preparation, synthetic data strategies, and validating model performance and safety in cloud environments.

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