Senior ML Engineer: Lead Production ML & Client Tech

Promtior; Buenos Aires; Híbrido; ARS 135.892.000 - 196.289.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

20 paid days off per year

Hybrid work model

Flex Days: monthly team activities

Professional development courses

Internal clubs

Descripción de la vacante

Promtior is seeking a Senior Machine Learning Engineer to lead the design, development, and deployment of ML models in production. You will own the full model lifecycle, define scalable data/ML architectures, and set engineering standards.

You will mentor engineers, defend ML approaches to clients, and advance MLOps across teams. This client-facing role requires strong Python, ML libraries, and cloud deployment experience, with a focus on scalable, reliable AI solutions.

Formación

• Advanced or completed studies in Systems Engineering, Data Science, AI, or related fields.
• 5+ years of professional software or data engineering experience.
• 3+ years of hands-on experience developing and productionizing machine learning models.
• Strong, production-level command of Python and ML libraries (scikit-learn, TensorFlow, PyTorch, or others).
• Proven experience owning the full model lifecycle in production, including monitoring, performance degradation, and retraining strategies.
• Strong experience working with data (ETL, analysis, feature engineering) and building data and ML pipelines.
• Experience deploying and serving models in cloud environments (AWS, GCP, or Azure).
• Solid architecture and integration skills across APIs, backend, and services.
• Demonstrated experience acting as a technical reference: mentoring engineers, reviewing code, and owning technical decisions.
• Experience working directly with clients or technical stakeholders as the technical counterpart.
• Good command of Git and collaborative work in technical teams.
• Advanced English Level.

Responsabilidades

• Own the design, development, and deployment of machine learning models in production environments, including the full model lifecycle.
• Define the architecture of scalable data and ML systems and set team standards for evaluation, validation, testing, and monitoring.
• Make and justify core technical trade-offs between classical ML and generative/agentic approaches.
• Serve as the technical counterpart for clients, translating business problems into ML solutions.
• Mentor and unblock engineers, review their work, and drive MLOps adoption across teams.

Conocimientos

Python

ML model deployment

Client-facing

Mentoring engineers

Git

English

Educación

Advanced studies in Systems Engineering or Data Science

Herramientas

scikit-learn

TensorFlow

PyTorch

MLflow

Kubeflow

SageMaker

Docker

CI/CD

Descripción del empleo

Promtior is seeking a Senior Machine Learning Engineer to lead the design, development, and deployment of ML models in production. You will own the full model lifecycle, define scalable data/ML architectures, and set engineering standards.

You will mentor engineers, defend ML approaches to clients, and advance MLOps across teams. This client-facing role requires strong Python, ML libraries, and cloud deployment experience, with a focus on scalable, reliable AI solutions.