Remote Senior ML Ops Engineer — Data Ingestion & Cloud AI

Bluelight Consulting Llc; Neuquén; Remote; ARS 135,219,000 - 236,634,000; Full time

Benefits offered by this job

Long-term contract

Autonomy

High visibility

Global team

Flexible environment

Job summary

Coderio is hiring a Senior Machine Learning Ops Engineer to own the 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.

You will ensure the technical health of the ML lifecycle, optimize cloud performance and costs, and deliver high-quality, scalable solutions that drive business value within a remote-first, international team.

Qualifications

• Bachelor's degree or proven equivalent experience in data engineering or ML roles.
• Hands-on experience deploying ML solutions in production.
• Strong knowledge of Python, SQL and Spark.
• Experience with Docker, Git, Bash, FastAPI, Sagemaker Studio, Airflow, CloudFormation.

Responsibilities

• Architect and develop end-to-end ML solutions.
• Manage and automate ML lifecycle from development to production.
• Collaborate with data engineers and data scientists to scale solutions.
• Evaluate cloud architectures for performance and cost-efficiency.
• Interact with teams to understand business challenges and propose technical solutions.
• Communicate complex concepts clearly and mentor teams on new developments.

Skills

Python

SQL

Spark

Docker

Git

Bash scripting

FastAPI

Sagemaker Studio

Airflow

CloudFormation

AWS

GCP

Communication

Team player

Problem solving

Education

Bachelor's degree in software engineering / computer science

Tools

N/A

Job description

Coderio is hiring a Senior Machine Learning Ops Engineer to own the 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.

You will ensure the technical health of the ML lifecycle, optimize cloud performance and costs, and deliver high-quality, scalable solutions that drive business value within a remote-first, international team.