Machine Learning Engineer (AI)

TL;DR

Machine Learning Engineer (AI): Designing, developing, and deploying advanced machine learning models and data analysis systems to support real-time pricing and proprietary feature engineering. Focus on building production-grade MLOps pipelines, optimizing modeling infrastructure, and integrating LLM-driven automation to streamline internal workflows.

Location: Must be based in the U.S. (Fully remote)

Salary: From $196,776 per year

Company

hirify.global is a fintech platform unlocking the value of hirify.globalernative assets, starting with the trading-card market, backed by industry leaders and professional athletes.

What you will do

• Conduct applied research to design, train, and evaluate predictive and descriptive machine learning models.
• Manage the complete MLOps lifecycle, including experiment tracking, model versioning, and containerization.
• Maintain and optimize machine learning infrastructure, including cloud compute environments and distributed computation jobs.
• Develop AI-driven automation solutions using Large Language Models to streamline internal processes.
• Design and develop internal software tools and backend services to expose model insights and support data quality.
• Collaborate with business stakeholders to translate analytical requirements into scalable data-driven solutions.

Requirements

• Master’s degree in data science, economics, mathematics, or computer science.
• 1 year of professional experience in machine learning model design, training, and evaluation using Python.
• Experience with MLOps tools like MLflow, Docker, and CI/CD pipelines.
• 1 year of experience orchestrating workflows with Apache Airflow and managing cloud compute environments.
• 1 year of experience with SQL (PostgreSQL) and cloud data platforms like Snowflake.
• Experience developing backend services using FastAPI, REST, or GraphQL.

Culture & Benefits

• Fully remote work environment within the U.S.
• Opportunity to work on high-scale real-time pricing systems.
• Collaborative environment working across business and engineering teams.
• Backed by prominent investors and industry leaders.