Senior ML Engineer: Lead Production ML & Client Solutions

Promtior; Córdoba; Presencial; ARS 181.190.000 - 362.379.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

20 paid days off per year

Flex Days: monthly team activities

Internal clubs (soccer, padel, running

Descripción de la vacante

Promtior is seeking a Senior Machine Learning Engineer to lead the ML lifecycle for agentic AI solutions. You will own models from data processing to deployment, defend architecture to clients, and elevate the technical level of the team as we scale our global operation.

You will collaborate with clients and engineers, setting standards for evaluation, testing, and monitoring, while balancing accuracy, latency, and cost in production environments.

Formación

• 5+ years of professional software or data engineering experience.
• 3+ years of hands-on experience developing and productionizing machine learning models.
• Strong production-level Python and ML libraries knowledge.
• Experience deploying and serving models in cloud environments (AWS, GCP, or Azure).
• Mentoring engineers and owning technical decisions.

Responsabilidades

• Own design, development, and deployment of ML models in production.
• Define scalable data and ML system architecture and standards.
• Balance accuracy, cost, and latency when choosing modeling approaches.
• Translate business problems into ML solutions for clients and stakeholders.
• Mentor engineers and drive MLOps best practices across teams.

Conocimientos

Python

ML libraries

Git

English

Cloud environments

Educación

Advanced studies in Systems Eng./Data Science/AI

Herramientas

MLflow

Kubeflow

SageMaker

Docker

Descripción del empleo

Promtior is seeking a Senior Machine Learning Engineer to lead the ML lifecycle for agentic AI solutions. You will own models from data processing to deployment, defend architecture to clients, and elevate the technical level of the team as we scale our global operation.

You will collaborate with clients and engineers, setting standards for evaluation, testing, and monitoring, while balancing accuracy, latency, and cost in production environments.