Remote Senior ML Ops Engineer

Svitla Systems, Inc.; Municipio de Rincón de los Sauces; Remote; ARS 2,009,000 - 3,348,000; Full time

Benefits offered by this job

Long-term contract engagement

High visibility role

Ability to influence technical策略

Collaborative international team

Flexible, dynamic environment

Job summary

Coderio, a remote-first software company, is seeking 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 and deploy scalable models into production.

In an established engineering team, you will optimize cloud performance and cost, collaborate with data engineers and scientists across borders, mentor teammates, and influence technical strategy for MLOps and data architectures.

Qualifications

• Bachelor's degree in software engineering/Computer Science or proven equivalent experience in data engineering or machine learning roles.

Responsibilities

• Architect and develop robust, end-to-end machine learning solutions.
• Manage and automate the complete machine learning lifecycle, ensuring seamless transitions from development to production.
• Collaborate closely with data engineers and data scientists to create highly scalable solutions and integrate them with other technical areas across the software development life cycle.
• Work on cloud solutions, actively evaluating the performance and cost-efficiency of potential architectures.
• Interact with other teams and stakeholders to deeply understand business challenges and propose effective technical solutions.
• Communicate technical concepts clearly and teach teams how to properly use and adopt the new developments.

Skills

Python

SQL

Spark

MLOps

Education

Bachelor's degree in software engineering or Computer Science

Tools

Docker

Git

Bash scripting

FastAPI

SageMaker Studio

Airflow

CloudFormation

Job description

Coderio, a remote-first software company, is seeking 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 and deploy scalable models into production.

In an established engineering team, you will optimize cloud performance and cost, collaborate with data engineers and scientists across borders, mentor teammates, and influence technical strategy for MLOps and data architectures.