Remote ML Ops Engineer — AI/ML in Production

FullStack; Comisión de Fomento de Perú; Teletrabalho; ARS 181 747 000 - 272 620 000; Tempo integral

Vantagens oferecidas por esta oferta de emprego

Remote work

Education opportunities

Career growth

Resumo da oferta

FullStack is hiring a Machine Learning Operations Engineer for remote, project-based work with U.S. clients. You will join client teams and collaborate with designers and engineers to deploy AI/ML solutions in production environments.

Required: 3+ years in ML/MLOps, advanced English, and a four-year degree. Familiarity with CI/CD, cloud platforms, Python, and ML lifecycle tools is expected.

Qualificações

• 3+ years of professional software development with ML and MLOps.
• Advanced English is required.
• Four-year college degree required.
• Experience deploying ML models to production via APIs/endpoints.
• MLOps: model tracking, versioning, monitoring, lifecycle management.
• Hands-on with LLMs or Generative AI concepts.
• Solid infra knowledge: containerization, cloud, CI/CD.
• Python for ML development and production apps.
• Familiarity with ML lifecycle tools and data platforms is a plus.
• Experience with RAG, LangChain, or LangGraph is a plus.
• Ability to own work and align with client goals.

Responsabilidades

• Join our talent network and connect with U.S. clients for flexible, project-based development work as an ML Operations Engineer.
• You will integrate into our client's team and collaborate daily with designers and engineers.

Conhecimentos

Machine Learning

MLOps

English proficiency

API deployment

Python for ML

CI/CD

Containerization

Cloud platforms

Data platforms

LangChain

RAG

Agile/Scrum

Ownership

Formação académica

Bachelor's degree

Ferramentas

MLflow

Databricks

Snowflake

Spark

BigQuery

LangChain

Descrição da oferta de emprego

FullStack is hiring a Machine Learning Operations Engineer for remote, project-based work with U.S. clients. You will join client teams and collaborate with designers and engineers to deploy AI/ML solutions in production environments.

Required: 3+ years in ML/MLOps, advanced English, and a four-year degree. Familiarity with CI/CD, cloud platforms, Python, and ML lifecycle tools is expected.