Remote Part-Time MLOps Engineer — Equity & FinTech Impact

Bizmoni Corp.; Ciudad de México; Presencial; MXN 1.040.402 - 1.560.603; A tiempo parcial

Ventajas ofrecidas por este puesto de trabajo

Equity-based compensation

Fully remote role

Descripción de la vacante

Bizmoni Corp. is seeking a skilled MLOps Engineer to design, automate, and optimize machine learning infrastructure. You will bridge data science and operations, ensuring scalable, secure, and cost-efficient ML workflows from experimentation to production.

You will collaborate with data scientists and developers to deploy models, monitor production systems, and maintain reliability for global users. This is a fully remote, part-time role with equity-based compensation and a mission-driven

Formación

• Experience as MLOps Engineer or similar role in fintech or AI startups.
• Proficient in Python; familiarity with Java/Scala is a plus.
• Experience with ML pipelines and deployment tools.
• Hands-on with cloud services (AWS, Azure, GCP).
• Strong containerization and orchestration knowledge (Docker/Kubernetes).

Responsabilidades

• Design, build, and maintain end-to-end ML infrastructure for scalable deployments.
• Automate ML pipelines with Docker, Kubernetes, and CI/CD.
• Collaborate with data scientists and engineers to deploy models.
• Monitor production models with observability tools (Prometheus, Grafana, ELK).
• Manage cloud infrastructure for cost efficiency and reliability.
• Ensure security protocols for sensitive data in fintech.
• Provide ongoing maintenance for ML applications.

Conocimientos

Python

ML Frameworks

Cloud Services

Docker & Kubernetes

Git & CI/CD

Model Deployment

Remote Collaboration

Educación

Bachelor's or Master's in CS/DS

Herramientas

Docker

Kubernetes

MLflow

Airflow

Kubeflow

SageMaker

Descripción del empleo

Bizmoni Corp. is seeking a skilled MLOps Engineer to design, automate, and optimize machine learning infrastructure. You will bridge data science and operations, ensuring scalable, secure, and cost-efficient ML workflows from experimentation to production.

You will collaborate with data scientists and developers to deploy models, monitor production systems, and maintain reliability for global users. This is a fully remote, part-time role with equity-based compensation and a mission-driven