Machine Learning Engineer

Company Description

Generative Engine Optimization (GEO) Platform

ChatGPT, Perplexity, Google AI, and Gemini

Role Overview

Machine Learning Engineer

AI visibility analytics

Location:

Experience:

Key Responsibilities

• Model Development & Deployment: Build and deploy ML models to analyze AI search responses and detect platform-level trends.
• NLP & Intent Understanding: Develop natural language processing algorithms to interpret search intent, query classification, and citation patterns.
• Content Recommendation: Create recommendation engines for content and topic optimization based on AI search trends.
• Real-Time Monitoring: Implement real-time monitoring systems to track AI platform changes (e.g., search results, answer citations).
• Data Engineering (Bonus):
• Build scalable data pipelines to collect responses across multiple AI platforms.
• Manage real-time data ingestion from ChatGPT, Perplexity, Google AI, etc.
• Create and maintain data warehouses handling millions of search queries and responses.
• Ensure data quality, consistency, and normalization across platforms.
  

Required Skills & Experience

• Strong proficiency in Python for ML and data workflows.
• Experience with ML frameworks: TensorFlow or PyTorch.
• Hands-on experience with MLOps, including model deployment and monitoring.
• Familiarity with cloud platforms (AWS, GCP, Azure) for model hosting and data pipelines.
• Experience in API development for serving models in production.
• Bonus: Exposure to data engineering, ETL pipelines, and database management.
  

What We’re Looking For

• A builder who thrives in early-stage startup environments.
• Curious about LLMs, AI search, and recommendation systems.
• Excited to work with large-scale real-time data across multiple AI platforms.
• Someone who takes ownership, experiments fast, and can ship end-to-end ML solutions.
  

Why Join Us?

• Be part of a category-creating GEO platform at the intersection of AI, search, and data.
• Work with cutting-edge LLM and AI-driven ecosystems.
• Remote-first, flexible culture with a fast-moving team.