Applied ML Engineer: Personalization & Retrieval Systems

Not Disclosed; United States; Remote; USD 120,000 - 170,000; Full time

Benefits offered by this job

Medical insurance

Dental insurance

Vision insurance

Savings plan

Paid time off

Job summary

Not Disclosed in the United States is seeking a machine learning engineer to build and optimize models for classification, ranking, retrieval, and personalization.

You will work with Python, PyTorch, and JAX, deploy production-grade code, and monitor performance, latency, and cost to ship frequent improvements.

The role emphasizes practical, scalable ML in a production environment and requires a strong foundation in modern architectures.

Qualifications

• Strong ML foundations and neural architectures with hands-on production deployment.
• Experience with classification, ranking, retrieval or personalization.
• Proficient in production-quality code using Python, PyTorch and JAX.

Responsibilities

• Build and improve ML models for classification, ranking, retrieval, and personalization.
• Debug production issues and monitor model performance to ship improvements.
• Develop efficient classifiers and optimize accuracy, latency, and cost.

Skills

ML foundations

Neural architectures

Production deployment

Classification

Ranking

Retrieval systems

Personalization

Tools

Python

PyTorch

JAX

Job description

Not Disclosed in the United States is seeking a machine learning engineer to build and optimize models for classification, ranking, retrieval, and personalization.

You will work with Python, PyTorch, and JAX, deploy production-grade code, and monitor performance, latency, and cost to ship frequent improvements.

The role emphasizes practical, scalable ML in a production environment and requires a strong foundation in modern architectures.