Remote Senior MLOps Engineer End-to-End ML Architect

Fullstack; Neuquén; Remote; ARS 106,616,000 - 167,540,000; Full time

Benefits offered by this job

Long‑term contract engagement

Strategic and high-visibility role

Influence technical strategy (MLOps)

Collaborative international team

Flexible, fast-paced work environment

Job summary

Coderio is seeking a Senior Machine Learning Ops Engineer to own the ML architecture, development, and automation of end‑to‑end solutions. You will bridge data science and software engineering, evaluate cloud options, and deploy scalable models in production.

This hands‑on role focuses on ML lifecycle health, cloud cost efficiency, and delivering high‑quality, scalable solutions with business impact. Remote LATAM opportunity with international collaboration.

Qualifications

• Bachelor’s degree in software engineering/CS or equivalent experience in data engineering or ML roles.
• Hands‑on experience deploying ML solutions in production.
• Strong Python, SQL and Spark.skills
• Experience with cloud platforms: AWS and GCP; Docker and CI/CD.

Responsibilities

• Architect and develop end‑to‑end machine learning solutions.
• Manage and automate the ML lifecycle from development to production.
• Collaborate with data engineers/scientists to build scalable solutions.
• Evaluate cloud architectures for performance and cost efficiency.
• Interact with teams to align technical solutions with business needs.
• Mentor and evangelize best practices across the team.

Skills

Python

SQL

Spark

Docker

Git

Bash Scripting

FastAPI

SageMaker Studio

Airflow

CloudFormation

AWS

GCP

Education

Bachelor’s degree in software engineering or computer science

Tools

Docker

Git

Bash Scripting

FastAPI

SageMaker Studio

Airflow

CloudFormation

Job description

Coderio is seeking a Senior Machine Learning Ops Engineer to own the ML architecture, development, and automation of end‑to‑end solutions. You will bridge data science and software engineering, evaluate cloud options, and deploy scalable models in production.

This hands‑on role focuses on ML lifecycle health, cloud cost efficiency, and delivering high‑quality, scalable solutions with business impact. Remote LATAM opportunity with international collaboration.