Senior MLOps Architect – Hybrid & Observability Lead

Promtior; Córdoba; Hybride; ARS 90 873 000 - 151 455 000; Plein temps

Avantages offerts par ce poste

20 paid days off per year

Hybrid work model

Flex Days: monthly team activities

Professional development courses

Internal clubs (soccer, padel, running

cinema)

Résumé du poste

Promtior is seeking an experienced MLOps Engineer to serve as the senior technical referent for ML infrastructure, shaping training, deployment, monitoring and governance across multiple squads. You will drive reproducible pipelines, model lifecycle management and cost-aware operation in a demanding fintech context.

The role emphasizes hands-on design, cross-team collaboration and leadership, with a focus on reliable, auditable and scalable ML platforms and strong collaboration with product

Qualifications

• Solid experience owning or designing MLOps platforms or ML infrastructure used by multiple teams.
• Hands-on production ML workloads on Databricks including Feature Store, Unity Catalog, MLflow tracking and model lifecycle management.
• Experience building production-grade ML pipelines: tracking, training, registry, CI/CD for models/data, online and batch inference at scale.
• Strong background in distributed systems and data/stream processing (Spark, Flink).
• Familiarity with cloud-based ML platforms (SageMaker, Vertex AI) and container deployments.
• Strong observability for ML: metrics, logs, traces, data drift and quality checks.
• Ability to communicate infrastructure/AI trade-offs to non-technical stakeholders.

Responsabilités

• Define and evolve end-to-end ML platform architecture (data, training, registry, serving, monitoring, governance).
• Set standard patterns for reproducible training, experiment tracking, model packaging and promotion flows from dev to production.
• Balance reliability, performance and cost for ML workloads with SRE/Infra/FinOps.
• Review designs for models and data pipelines to meet platform standards and non-functional requirements.
• Mentor MLOps engineers on system design, reliability, CI/CD for ML; lead architecture reviews.

Connaissances

MLOps platform design

Databricks/Mlflow

Production ML workloads

Distributed systems

Cloud ML platforms

Observability for ML

Stakeholder communication

Outils

Unity Catalog

SageMaker/Vertex AI

Description du poste

Promtior is seeking an experienced MLOps Engineer to serve as the senior technical referent for ML infrastructure, shaping training, deployment, monitoring and governance across multiple squads. You will drive reproducible pipelines, model lifecycle management and cost-aware operation in a demanding fintech context.

The role emphasizes hands-on design, cross-team collaboration and leadership, with a focus on reliable, auditable and scalable ML platforms and strong collaboration with product