Senior ML Ops Engineer - Remote & Impactful

Agileengine, Llc.; Municipio de Rincón de los Sauces; Remote; ARS 181,747,000 - 242,329,000; Full time

Benefits offered by this job

Remote-first culture

Flexible hours

Job summary

Coderio is a remote-first company delivering scalable digital solutions to global clients. We seek a Senior ML Ops Engineer to own architecture, development and automation of end-to-end ML solutions, bridging data science and software engineering for production deployment.

You will deploy models, optimize cloud architecture for performance and cost, and collaborate with data engineers and scientists to deliver scalable, business-focused outcomes.

Qualifications

• Bachelor’s degree in software engineering or computer science, or equivalent experience.
• Hands-on experience deploying ML solutions in production.
• Advanced Python, SQL, and Spark proficiency.
• Experience with Docker, Git, Bash, FastAPI, Sagemaker Studio, Airflow, CloudFormation.
• Strong data architecture and systems integration knowledge.
• Excellent problem solving and collaboration skills.
• Extensive experience with AWS and GCP.
• Team player with clear communication.

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 scale solutions.
• Evaluate cloud architectures for performance and cost.
• Align with business challenges and propose technical solutions.
• Mentor and advocate for new developments within 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 a remote-first company delivering scalable digital solutions to global clients. We seek a Senior ML Ops Engineer to own architecture, development and automation of end-to-end ML solutions, bridging data science and software engineering for production deployment.

You will deploy models, optimize cloud architecture for performance and cost, and collaborate with data engineers and scientists to deliver scalable, business-focused outcomes.