Senior ML Ops Engineer - Remote Production ML & Cloud Lead

Bluelightconsulting; Municipio de Rincón de los Sauces; Remote; ARS 181.906.000 - 272.860.000; Vollzeit

Benefits dieser Stelle

Remote-first

Autonomy

High-visibility role

International team

Zusammenfassung

Coderio seeks a Senior Machine Learning Ops Engineer to own the architecture, development, and automation of end-to-end ML solutions. You will bridge data science and software engineering, evaluate cloud options, and deploy scalable models into production from an established engineering team.

You will optimize ML lifecycle health, cloud performance and cost-efficiency, and deliver high-quality scalable solutions driving business value in a hands-on role.

Qualifikationen

• Bachelor’s degree in software engineering/CS or proven equivalent in data engineering or ML roles.
• Hands-on experience deploying ML solutions in production.
• Strong Python, SQL, and Spark basics.
• Experience with Docker, Git, Bash, FastAPI, SageMaker Studio, Airflow and CloudFormation.
• Solid data architectures and complex system integration knowledge.
• Strong problem solving and communication skills.
• Extensive experience with AWS and GCP cloud platforms.

Aufgaben

• Architect and develop end-to-end ML solutions.
• Manage and automate the ML lifecycle from development to production.
• Collaborate with data engineers and data scientists to build scalable solutions.
• Evaluate cloud architectures for performance and cost-efficiency.
• Interact with teams to align technical work with business goals.
• Mentor and advocate for best practices in ML engineering.

Kenntnisse

Python

SQL

Soft skills / communication

ML deployment

Ausbildung

Bachelor's degree in Software Engineering or CS

Tools

Docker

Git

Bash scripting

FastAPI

SageMaker Studio

Airflow

CloudFormation

Jobbeschreibung

Coderio seeks a Senior Machine Learning Ops Engineer to own the architecture, development, and automation of end-to-end ML solutions. You will bridge data science and software engineering, evaluate cloud options, and deploy scalable models into production from an established engineering team.

You will optimize ML lifecycle health, cloud performance and cost-efficiency, and deliver high-quality scalable solutions driving business value in a hands-on role.