Senior ML Ops Engineer — Remote & Cloud-Scale AI

Silver.Dev; Municipio de Rincón de los Sauces; Remote; ARS 1,800,000 - 3,000,000; Full time

Benefits offered by this job

Remote-friendly

High impact

International team

Autonomy

Job summary

Coderio, a remote-first engineering company, seeks a Senior ML Ops Engineer to own 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.

This hands-on role focuses on ML lifecycle health, cloud cost-efficiency, and delivering high-quality, scalable outcomes that drive business value. You will mentor teams and help shape technical strategy.

Qualifications

• Bachelor's degree in software engineering or computer science or proven equivalent experience in data engineering or ML roles.
• Proven hands-on experience implementing and deploying ML solutions in production environments.
• Advanced knowledge of Python, SQL, and Spark.
• Strong knowledge of Docker, Git, Bash, FastAPI, Sagemaker Studio, Airflow, and CloudFormation.
• Solid understanding of data architectures and complex systems integration.
• Excellent communication skills and teamwork.

Responsibilities

• 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.
• Engage with cross-functional teams to align technical solutions with business goals.
• Mentor and advocate for best practices in ML engineering.

Skills

Python

SQL

Spark

MLOps

Education

Bachelor's degree in software engineering or CS

Tools

Docker

Git

Bash

FastAPI

Sagemaker Studio

Airflow

CloudFormation

Job description

Coderio, a remote-first engineering company, seeks a Senior ML Ops Engineer to own 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.

This hands-on role focuses on ML lifecycle health, cloud cost-efficiency, and delivering high-quality, scalable outcomes that drive business value. You will mentor teams and help shape technical strategy.