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Lunon

AI-powered consulting building client AI systems

Forward Deployed AI Engineer

Applied Machine LearningConfirmed live in the last 24 hours
Full-timeRemote in USA$180k - $210k /yr

About the Job

Requirements

  • You have fine-tuned or post-trained a model and can explain what worked and what did not.
  • You have built evaluations that changed a decision.
  • You have shipped large language model features that people depend on.
  • You have served a model in production and owned its cost and latency.
  • You work with artificial intelligence coding tools every day and judge the result by the system it produces.

Responsibilities

  • Choose the right model for each problem, from frontier application programming interfaces to open-weight models, and know when fine-tuning outperforms a better prompt.
  • Fine-tune where it pays off, including supervised fine-tuning, preference optimization, and parameter-efficient methods such as low-rank adaptation.
  • Design the evaluations and benchmarks that show whether a change made things better.
  • Take models from training to serving, balancing cost, latency, and quality.
  • Work with the company's team to find where artificial intelligence will change their results most, and decline work that will not repay the effort.

Desired Qualifications

  • Have built on or integrated with an enterprise resource planning, customer relationship management, or accounting system.
  • Have shipped extraction or search over complex business documents.
  • Have done consulting or forward-deployed work, and know how to earn trust inside a company that is not yours.

About the Company

Lunon

AI-powered consulting building client AI systems

Lunon embeds engineers with client teams to build AI systems on the client’s own data and workflows, putting them into daily use and delivering client-ready research, analysis, and outputs in days rather than weeks. Engineers work inside the client team, creating AI solutions that fit existing data and processes, and hand them over once they are functioning. The company differentiates itself by providing on-site-like, AI-native engineering teams that move quickly from concept to deployed, usable systems on the client’s data, rather than offering generic tools or external consulting. Its goal is to deliver operational AI systems that clients can adopt and rely on, completed in a matter of days and handed over for ongoing use.

Company size
1-10
Company stage
Not listed
Total funding
Not listed
Headquarters
New York City, New York
Founded
2025

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