Python & Kubernetes Data Engineer for AI/ML & Analytics

Canonical; A distancia; MXN 400,000 - 600,000; Jornada completa

Descripción de la vacante

A leading open source technology provider is seeking specialists in Python and Kubernetes to develop data analytics and MLOps solutions. You'll work remotely with a global team while engaging in innovative projects that focus on open-source technology, public cloud, and private infrastructure. Ideal candidates are self-motivated and possess an undergraduate degree in a technical field, proficient in Python and familiar with Linux systems. Benefits include competitive pay, bonuses, and a learning budget.

Servicios

Personal learning and development budget of USD 2,000 per year

Annual compensation review

Employee Assistance Programme

Twice-yearly team sprints in person

Formación

• Track record of going above-and-beyond expectations to achieve outstanding results.
• Passion for technology evidenced by personal projects and initiatives.
• Ability to travel twice a year for company events.

Responsabilidades

• Develop your understanding of the entire Linux stack.
• Design, build and maintain solutions for public and private clouds.
• Collaborate with a distributed team of engineers.

Conocimientos

Professional or academic software delivery using Python

Experience with Linux (Debian or Ubuntu preferred)

Excellent interpersonal skills

Professional written and spoken English

Experience with container technologies (Docker, Kubernetes)

Educación

Undergraduate degree in a technical subject

Descripción del empleo

A leading open source technology provider is seeking specialists in Python and Kubernetes to develop data analytics and MLOps solutions. You'll work remotely with a global team while engaging in innovative projects that focus on open-source technology, public cloud, and private infrastructure. Ideal candidates are self-motivated and possess an undergraduate degree in a technical field, proficient in Python and familiar with Linux systems. Benefits include competitive pay, bonuses, and a learning budget.