Remote MLOps Engineer — AI/ML in Production

FullStack; Mar del Plata; Remote; ARS 1,800,000 - 3,000,000; Full time

Benefits offered by this job

Remote work

Career growth

Continuing education

Competitive pay

Job summary

FullStack in Argentina is seeking a Machine Learning Operations Engineer to join our network and work on deployment-ready AI projects for US clients. You will collaborate with client teams and engineers, applying MLOps best practices to production environments.

The role requires hands-on Python, ML tooling, and familiarity with LangChain or RAG, with advanced English and a four-year degree. This opportunity offers fully remote work and exposure to leading startups and Fortune 500 companies.

Qualifications

• 3+ years of professional software development experience with ML and MLOps.
• Advanced English is required.
• Four-year college degree is required.
• Experience deploying ML/AI models to production via APIs/endpoints.
• Practical MLOps: model tracking, versioning, monitoring, lifecycle.
• Hands-on with LLMs or Generative AI concepts.
• Infra fundamentals: containers, cloud, CI/CD.
• Python for ML development and automation.
• Experience with ML lifecycle tools (MLflow) and data platforms (Databricks, Snowflake, Spark, BigQuery) a plus.
• Experience with RAG, LangChain, or LangGraph a plus.
• Ability to own and deliver on commitments in Agile environments.
• Strong problem solving and collaboration in distributed teams.

Responsibilities

• Join client teams and work with designers and engineers on ML/AI deployments.
• Collaborate across ML tooling and production environments to deliver value.

Skills

ML/MLOps experience

Python programming

CI/CD

Agile/Scrum

English proficiency

Education

Bachelor's degree

Tools

MLflow

Databricks

Snowflake

Spark

BigQuery

LangChain

LangGraph

Job description

FullStack in Argentina is seeking a Machine Learning Operations Engineer to join our network and work on deployment-ready AI projects for US clients. You will collaborate with client teams and engineers, applying MLOps best practices to production environments.

The role requires hands-on Python, ML tooling, and familiarity with LangChain or RAG, with advanced English and a four-year degree. This opportunity offers fully remote work and exposure to leading startups and Fortune 500 companies.