Remote MLOps Engineer for AI/ML Production

FullStack; La Plata; Remote; ARS 136,310,000 - 227,183,000; Full time

Benefits offered by this job

100% remote work

Continuing education

Growth opportunities

Job summary

FullStack is seeking a Machine Learning Operations Engineer (AI/ML) to join our talent network and collaborate with US client teams on flexible, project-based work. You’ll apply MLOps practices, deploy models to production, and contribute to cloud, data, and AI pipelines in a fully remote, international setting.

You’ll join a diverse team delivering AI-enhanced software for leading startups and Fortune 500s, with opportunities for growth and continuous learning.

Qualifications

• 3+ years of professional software development experience with Machine Learning and MLOps practices.
• Advanced English is required.
• Four-year college degree is required.
• Proven experience deploying ML/AI models to production via APIs or endpoints.
• Experience with model tracking, versioning, monitoring, and lifecycle management.
• Hands-on experience with LLMs or Generative AI concepts.
• Solid understanding of containerization, cloud platforms, and CI/CD workflows.
• Proven experience with Python for ML development and production apps.
• Experience with AI/ML lifecycle tools and data platforms is a plus.
• Experience with agentic workflows or Retrieval-Augmented Generation is a plus.

Responsibilities

• Integrate into the client’s team and collaborate daily with designers and engineers.
• Deploy ML/AI models to production via APIs or endpoints.
• Contribute to scalable, reliable AI pipelines and infrastructure.

Skills

Machine Learning

MLOps

Python

LLMs

CI/CD

Cloud platforms

Containerization

Agile/Scrum

Advanced English

APIs/Endpoints

Education

Bachelor's degree

Tools

MLflow

Databricks

Snowflake

Spark

BigQuery

LangChain

LangGraph

Job description

FullStack is seeking a Machine Learning Operations Engineer (AI/ML) to join our talent network and collaborate with US client teams on flexible, project-based work. You’ll apply MLOps practices, deploy models to production, and contribute to cloud, data, and AI pipelines in a fully remote, international setting.

You’ll join a diverse team delivering AI-enhanced software for leading startups and Fortune 500s, with opportunities for growth and continuous learning.