Senior ML Ops Engineer — Build Scalable Production ML

Improving South America; Municipio de Rincón de los Sauces; Remote; ARS 166,601,000 - 257,474,000; Full time

Benefits offered by this job

Remote-first company

Autonomy in role

Competitive compensation

Job summary

Coderio designs and delivers scalable digital solutions for global companies. We are seeking a Senior Machine Learning Ops Engineer to own the architecture, development, and automation of end-to-end ML solutions, bridging data science and software engineering in a hands-on role.

You will optimize the ML lifecycle health, cloud performance and cost, and work with data engineers and scientists to deploy robust models. This remote-first role offers autonomy and opportunities to shape MLOps strategy.

Qualifications

• Bachelor’s degree in software engineering or computer science, or 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.

Responsibilities

• Architect and develop end-to-end machine learning solutions.
• Manage and automate the complete ML lifecycle from development to production.
• Collaborate with data engineers and scientists to create scalable solutions and integrate with other areas of SDLC.
• Work on cloud solutions, evaluating performance and cost-efficiency of architectures.
• Interact with teams to understand business challenges and propose technical solutions.
• Communicate concepts clearly and mentor teams on new developments.

Skills

Python

SQL

Spark

Soft skills

Team collaboration

Communication

Education

Bachelor’s degree in software engineering/computer science

Tools

Docker

Git

Bash Scripting

FastAPI

Sagemaker Studio

Airflow

CloudFormation

Job description

Coderio designs and delivers scalable digital solutions for global companies. We are seeking a Senior Machine Learning Ops Engineer to own the architecture, development, and automation of end-to-end ML solutions, bridging data science and software engineering in a hands-on role.

You will optimize the ML lifecycle health, cloud performance and cost, and work with data engineers and scientists to deploy robust models. This remote-first role offers autonomy and opportunities to shape MLOps strategy.