Senior ML Engineer: Real-Time Bidding on a Scalable Platform

Jampp; Argentina; Híbrido; ARS 1.800.000 - 3.000.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Extended maternity/paternity leaves

Extended holidays

Office and remote work balance

Structured remote onboarding

Continuous training and team learning

Global team collaboration

Swag and team activities

Descripción de la vacante

Jampp is seeking a Senior Machine Learning Engineer to own and optimize parts of our machine-learning platform that predicts bids in under 20 milliseconds for our auction-based ad system.

You will collaborate with data scientists, data engineers, and software engineers to build scalable distributed systems, improve model training pipelines, and ensure low-latency predictions across global campaigns.

Formación

• 5+ years hands-on experience building software in Python.
• Strong CS fundamentals and production-grade coding.
• Experience with ML technologies and model training pipelines.
• Comfortable writing production-ready code with quality results quickly.
• Experience with AWS; Kubernetes is a plus.
• Good SQL and database knowledge (Trino SQL a plus).
• Excellent communication in English and Spanish.

Responsabilidades

• Design, code and deploy scalable features for a machine-learning platform.
• Visualize statistical concepts and model performance.
• Evaluate models with a focus on scalability and trade-offs.
• Adapt ML methods to parallel environments.
• Collaborate with data scientists, data engineers and software engineers.
• Work autonomously with a strong ownership mindset.
• Learn and teach state-of-the-art ML technologies.

Conocimientos

Python

CS fundamentals

ML pipelines

SQL

English

Spanish

AWS

Kubernetes

Herramientas

C++

Go

Trino SQL

AWS

Descripción del empleo

Jampp is seeking a Senior Machine Learning Engineer to own and optimize parts of our machine-learning platform that predicts bids in under 20 milliseconds for our auction-based ad system.

You will collaborate with data scientists, data engineers, and software engineers to build scalable distributed systems, improve model training pipelines, and ensure low-latency predictions across global campaigns.