Machine Learning Engineer (MLOps)

Proofpoint; Córdoba; Presencial; ARS 104.359.234 - 163.993.082; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Competitive compensation

Comprehensive benefits

Flexible work environment

Global collaboration

Descripción de la vacante

Proofpoint, a global leader in cybersecurity, is seeking a Machine Learning Engineer in Argentina to design, build, and scale production ML systems for real-time threat detection. You will own the full ML lifecycle—from data pipelines and feature engineering to model training, serving, and monitoring at scale.

You will collaborate with data scientists, data engineers, and security teams to deliver robust solutions and ensure production excellence.

Formación

• 3–4 years of software engineering and ML systems experience.
• Strong Python programming and fundamentals in data structures and algorithms.
• Hands-on experience with ML frameworks in production (PyTorch, TensorFlow, Scikit-learn).
• Familiarity with ML deployment/serving frameworks (MLflow, TensorFlow Serving, KServe) and cloud platforms.

Responsabilidades

• Design and build scalable ML pipelines and data infrastructure for high-throughput threat detection.
• Own end-to-end deployment and monitoring of ML models in production, including A/B testing.
• Architect model serving solutions (REST APIs, batch prediction, streaming) to meet latency needs.
• Build feature pipelines and data infra to support training and inference at scale.
• Collaborate with data scientists to translate model requirements into production systems.
• Implement monitoring, logging, and alerting for ML models in production.
• Optimize model performance and manage compute costs and latency tradeoffs.

Conocimientos

Python

Data structures & algorithms

System design

ML pipelines

PyTorch/TensorFlow/Scikit-learn

AWS

CI/CD

Herramientas

MLflow

TensorFlow Serving

KServe

GoLang

AWS (EC2, S3, SageMaker)

Descripción del empleo

About Us

Proofpoint is a global leader in human- and agent-centric cybersecurity. We protect how people, data, and AI agents connect across email, cloud, and collaboration tools. Over 80 of the Fortune 100, 10,000 large enterprises, and millions of smaller organizations trust Proofpoint to stop threats, prevent data loss, and build resilience across their people and AI workflows. Our mission is simple safeguard the digital world and empower people to work securely and confidently. Join us in our pursuit to defend data and protect people.

About Us

Proofpoint is a global leader in human- and agent-centric cybersecurity. We protect how people, data, and AI agents connect across email, cloud, and collaboration tools. Over 80 of the Fortune 100, 10,000 large enterprises, and millions of smaller organizations trust Proofpoint to stop threats, prevent data loss, and build resilience across their people and AI workflows. Our mission is simple safeguard the digital world and empower people to work securely and confidently. Join us in our pursuit to defend data and protect people.

How We Work

• Bold in how we dream and innovate
• Responsive to feedback, challenges and opportunities
• Accountable for results and best in class outcomes
• Visionary in future focused problem-solving
• Exceptional in execution and impact

We are seeking a Machine Learning Engineer with at least 3-4 years of software engineering and ML systems experience to join our collaborative Machine Learning Engineering Team at Proofpoint. This role is integral to designing, building, and scaling production ML systems for cybersecurity challenges. You will take ownership of the full ML lifecycle—from data pipelines and feature engineering to model training, serving, and monitoring at scale. You will work closely with data scientists, data engineers, and security teams to build robust, performant systems that detect and prevent cyber threats in real time.

What You Bring to the Team

As a core team member, you will play a crucial role in architecting scalable ML systems and ensuring production excellence. You will own the end-to-end development and deployment of ML models, from infrastructure design to optimization and monitoring. You work closely with data scientists, MLOps engineers, data engineers, and security specialists to ensure models scale, perform reliably, and integrate seamlessly into our production environments.

Day-to-Day Responsibilities

• Design and build scalable ML pipelines and data infrastructure for high-throughput threat detection systems.
• Own the end-to-end deployment and monitoring of ML models in production, including A/B testing and performance optimization.
• Architect model serving solutions (REST APIs, batch prediction, streaming) that meet latency and throughput requirements.
• Build feature pipelines and data infrastructure to support model training and inference at scale.
• Collaborate with data scientists to understand model requirements and translate them into production systems.
• Implement monitoring, logging, and alerting for ML models in production to detect performance degradation and failures.
• Optimize model performance and resource utilization, managing compute costs and inference latency tradeoffs.
• Actively engage with the team including data scientists, engineers, ML platform specialists, security analysts, and product management to deliver robust solutions.

Desired Skills & Experience

• Strong software engineering fundamentals proficiency in Python, solid understanding of data structures, algorithms, and system design.
• Experience building ML systems end-to-end data pipelines, feature engineering, model training, model serving, and monitoring.
• Hands-on experience with ML frameworks PyTorch, TensorFlow, or Scikit-learn in production settings.
• Familiarity with ML deployment and serving frameworks MLflow, TensorFlow Serving, KServe, or similar.
• Familiarity with goLang
• Experience with cloud platforms, particularly AWS (EC2, S3, SageMaker, Lambda, RDS) for building scalable systems.
• Understanding of software engineering best practices testing, CI/CD, code review, and version control.
• Basic understanding of adversarial ML concepts and security analytics is a plus.

Why Proofpoint?

At Proofpoint, we believe that an exceptional career experience includes a comprehensive compensation and benefits package. Here are just a few reasons you’ll love working with us

• Competitive compensation
• Comprehensive benefits
• Career success on your terms
• Flexible work environment
• Annual wellness and community outreach days
• Always on recognition for your contributions
• Global collaboration and networking opportunities

Our Culture

Our culture is rooted in values that inspire belonging, empower purpose and drive success-every day, for everyone.

We encourage applications from individuals of all backgrounds, experiences, and perspectives. If you need accommodation during the application or interview process, please reach out to [e-mail].