Senior ML Engineer — End-to-End Production AI (Remote)

Aimlroles; Northern (KY); Hybrid; USD 153,000 - 198,000; Full time

Benefits offered by this job

401(k) plan

Unlimited PTO

Health insurance

WeWork memberships (select markets)

Monthly mobile/internet stipend

Annual lifestyle stipend

Job summary

Button is seeking a Senior Machine Learning Engineer to own the end-to-end ML lifecycle, including data pipelines, training workflows, deployment, inference services, monitoring, and retraining. You will collaborate with product managers, data scientists, and software engineers to translate business problems into reliable production ML systems powering real product decisions.

You will design scalable data pipelines and feature stores, build models for ranking and recommendations, and ensure

Qualifications

• 5+ years of professional ML engineering or data engineering experience.
• Fluency with Python and SQL.
• Experience designing and operating data pipelines at scale.
• Hands-on deployment of ML models in production.
• Experience with AWS and cloud services.

Responsibilities

• Own the full ML lifecycle from data pipelines to deployment and retraining.
• Design reliable data and feature pipelines and feature stores.
• Build and optimize models including ranking and recommender systems.
• Implement batch scoring and online inference with latency targets.
• Collaborate with data scientists and software engineers for production integration.
• Establish observability and monitor data freshness and model performance.
• Mentor teammates and promote ML engineering best practices.

Skills

Python

SQL

Airflow

dbt

AWS

PyTorch

TensorFlow

Scikit-learn

Data pipelines

Tools

Amazon SageMaker

Redis

Spark

Streaming systems

Job description

Button is seeking a Senior Machine Learning Engineer to own the end-to-end ML lifecycle, including data pipelines, training workflows, deployment, inference services, monitoring, and retraining. You will collaborate with product managers, data scientists, and software engineers to translate business problems into reliable production ML systems powering real product decisions.

You will design scalable data pipelines and feature stores, build models for ranking and recommendations, and ensure