Remote Senior ML Ops Engineer — Scale AI in Production

Fullstack; Neuquén; Remote; ARS 136.430.000 - 197.065.000; Vollzeit

Benefits dieser Stelle

Long-term contract

High impact role

Influence strategy

International team

Remote-first

Zusammenfassung

Coderio is seeking a Senior Machine Learning Ops Engineer for a long-term remote engagement. You will architect end-to-end ML solutions, manage the ML lifecycle from development to production, and collaborate with data engineers and data scientists to scale systems.

You’ll work with AWS and GCP, use Python, SQL, Spark, and tools like Docker, Airflow, SageMaker Studio, and FastAPI. A Bachelor’s degree in CS or software engineering is expected, plus strong communication and problem-solving skills.

Qualifikationen

• Bachelor’s degree in software engineering or Computer Science or proven equivalent experience in data engineering or ML roles.
• Hands-on experience deploying ML solutions in production environments.
• Strong knowledge of Python, SQL and Spark.
• Experience with AWS and GCP cloud platforms and modern ML tooling.

Aufgaben

• Architect and develop end-to-end machine learning solutions.
• Manage and automate the full ML lifecycle from development to production.
• Collaborate with data engineers and data scientists to build scalable systems.
• Evaluate cloud architectures for performance and cost efficiency.
• Engage with stakeholders to align technical work with business goals.
• Mentor and advocate best practices within the team.

Kenntnisse

Python

SQL

Spark

Team player

Communication

Ausbildung

Bachelor’s degree in software engineering or Computer Science

Tools

Docker

Git

Bash scripting

FastAPI

Sagemaker Studio

Airflow

CloudFormation

Jobbeschreibung

Coderio is seeking a Senior Machine Learning Ops Engineer for a long-term remote engagement. You will architect end-to-end ML solutions, manage the ML lifecycle from development to production, and collaborate with data engineers and data scientists to scale systems.

You’ll work with AWS and GCP, use Python, SQL, Spark, and tools like Docker, Airflow, SageMaker Studio, and FastAPI. A Bachelor’s degree in CS or software engineering is expected, plus strong communication and problem-solving skills.