Senior ML Engineer, MLOps & Forecasting

Apella; United States; Teletrabalho; USD 150 000 - 210 000; Tempo integral

Vantagens oferecidas por esta oferta de emprego

Competitive salary and stock options

Remote-first work environment

Resumo da oferta

Apella is applying computer vision and machine learning to improve the standard of care in surgery. We’re seeking a senior ML engineer who would thrive at the intersection of MLOps, infrastructure, and production forecasting systems.

You excel at building robust, automated ML pipelines that enable data scientists to iterate quickly while maintaining the reliability that our healthcare customers depend on. You are a systems thinker who flourishes in a startup environment, working across the stack

Qualificações

• 5+ years of experience building and maintaining production ML systems.
• Deep expertise in MLOps, deployment automation, and model serving infrastructure.
• Strong software engineering skills with Python and containerization.

Responsabilidades

• Collaborate with engineering, product, and data science teams on ML solutions.
• Develop tools to automate manual processes and improve efficiency.
• Build, integrate, and monitor end-to-end lifecycles of large-scale ML systems.
• Investigate model performance and data quality issues.
• Enhance ML pipeline for forecasting platform with weekly retraining and deployment.
• Elevate team capabilities in MLOps and production ML systems.

Conhecimentos

Python

MLOps

Docker

Kubernetes

CI/CD

Terraform

Helm

API design

Microservices

Production ML

Ferramentas

Dagster

Airflow

Descrição da oferta de emprego

Apella is applying computer vision and machine learning to improve the standard of care in surgery. We’re seeking a senior ML engineer who would thrive at the intersection of MLOps, infrastructure, and production forecasting systems.

You excel at building robust, automated ML pipelines that enable data scientists to iterate quickly while maintaining the reliability that our healthcare customers depend on. You are a systems thinker who flourishes in a startup environment, working across the stack