Staff Machine Learning Engineer - Production ML (Remote US)

Grailed, LLC; United States; Remote; USD 159,040 - 233,800; Full time

Benefits offered by this job

401K

Paid time off

Dental

Medical

Vision

Disability insurance

Life insurance

Job summary

Grailed, LLC is seeking a Staff Machine Learning Engineer to own end-to-end ML systems in production, from architecture through monitoring, in a fast-growing fashion marketplace. This hands-on role requires taking ownership across the entire lifecycle, including training, deployment, and reliability.

You will build and operate systems that drive search ranking, recommendations, and feed ordering, while collaborating with data science, data engineering, product management, and backend teams.

Qualifications

• 7+ years of engineering experience in production ML systems.
• End-to-end ownership from training to deployment.
• Advanced knowledge of ML/AI for ecommerce.
• Strong proficiency in Python; SQL; DBT; Airflow.
• Solid software engineering fundamentals.
• Experience with ranking, retrieval, or recommendation systems.
• Expertise with ML lifecycle tooling and modern data infrastructure.

Responsibilities

• Own the full lifecycle of predictive models in production—from architecture to deployment.
• Build and operate systems routing model outputs to search, ranking, and recommendations surfaces.
• Establish model monitoring, drift detection, and retraining cadences.
• Collaborate with DS, Data Eng, PM, and backend engineers to move validated work to production.
• Decide when to leverage external ML infrastructure versus in-house solutions.
• Contribute to ML infrastructure decisions including serving architecture and pipelines.

Skills

End-to-end ownership

Python

SQL

DBT

Airflow

Ranking systems

ML lifecycle tooling

Production ML

Tools

Experiment tracking

Model versioning

Pipeline orchestration

Job description

Grailed, LLC is seeking a Staff Machine Learning Engineer to own end-to-end ML systems in production, from architecture through monitoring, in a fast-growing fashion marketplace. This hands-on role requires taking ownership across the entire lifecycle, including training, deployment, and reliability.

You will build and operate systems that drive search ranking, recommendations, and feed ordering, while collaborating with data science, data engineering, product management, and backend teams.