Staff Full Stack Machine Learning Engineer

Cordoba, Argentina

Proofpoint

Proofpoint helps protect people, data and brands against cyber attacks. Offering compliance and cybersecurity solutions for email, web, cloud, and more.

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It's fun to work in a company where people truly BELIEVE in what they're doing!

We're committed to bringing passion and customer focus to the business.

Corporate Overview

Proofpoint is a leading cybersecurity company protecting organizations’ greatest assets and biggest risks: vulnerabilities in people. With an integrated suite of cloud-based solutions, Proofpoint helps companies around the world stop targeted threats, safeguard their data, and make their users more resilient against cyber-attacks. Leading organizations of all sizes, including more than half of the Fortune 1000, rely on Proofpoint for people-centric security and compliance solutions mitigating their most critical risks across email, the cloud, social media, and the web.

We are singularly devoted to helping our customers protect their greatest assets and biggest security risk: their people. That’s why we’re a leader in next-generation cybersecurity. Protection Starts with People. 

The Role

 We're seeking a Staff Full-Stack Machine Learning Engineer with a minimum of 5 years of relevant experience to join our unified Scrum team. This team is responsible for everything from ETL processes and Data Science to MLOps, in an end-to-end framework. In this multifaceted role, you'll serve as both a technical linchpin and a mentor, steering best practices throughout the complete machine learning lifecycle.

 

What you bring to the team 

Your extensive experience will enable you to shape the architectural design of our robust, scalable solutions. Responsibilities will include building and maintaining data pipelines, ensuring a seamless data flow for our machine learning models, and translating project management requirements into actionable ML initiatives. Since we operate as a unified team, you'll work closely with members specializing in data science, MLOps, and ETL to ensure our models are well-crafted, scalable, and operationally sound. Ideally, you're proficient in the entire ML pipeline but excel particularly in machine learning aspects. Exposure to the challenges of adversarial machine learning would be a plus. Your leadership will be pivotal in fostering a culture of best practices within our comprehensive machine learning Scrum team. You'll guide us in constructing systems resilient to adversarial attacks, enhancing the reliability and safety of our solutions. Proactively identifying areas for improvement, you will propose actionable solutions and lead our focused team in executing them for operational excellence.

Day to day

Throughout the day, you might collaborate closely with other data scientists to ensure that machine learning models are not just theoretically sound but also practical for scalable, real-world applications. You may also spend time reviewing code, running tests, and debugging issues that arise in different parts of the ML pipeline. As someone responsible for mentoring and leading best practices, you'll frequently consult with team members to help them overcome technical challenges. This might involve one-on-one mentoring or leading focused group discussions to resolve complex issues. Given your expertise in cloud platforms like AWS, part of your day might also be spent deploying models to production environments, setting up monitoring systems, or automating workflows using MLOps best practices. Your days will be a blend of hands-on coding, team collaboration, problem-solving, and leadership activities, all aimed at achieving operational excellence and pushing the boundaries of what our machine learning systems can do.

 

Desired Skills:

  • Strong proficiency in Python and/or PySpark, coupled with hands-on experience in machine learning frameworks like TensorFlow or PyTorch.

  • Experience with large language models like BERT, GPT, or similar, as well as off-the-shelf ML algorithms.

  • Expertise in cloud computing platforms, especially AWS services like EC2, S3, Lambda, Glue, and particularly SageMaker, for building, deploying, and scaling machine learning solutions.

  • In-depth understanding of ETL processes, including data collection, cleaning, and transformation to ensure effective data pipelines.

  • Demonstrated leadership in promoting best practices in MLOps, including CI/CD, model versioning, and monitoring for operational excellence.

  •  Familiarity with adversarial machine learning, including an understanding of related security considerations, model robustness, and data integrity.

Why Proofpoint

As a customer focused and driven-to-win organization with leading edge products, there are many exciting reasons to join the Proofpoint team. We believe in hiring the best the brightest and cultivating a culture of collaboration and appreciation. As we continue to grow and expand globally, we understand that hiring the right people and developing great teams is key to our success! We are a multi-national company with locations in many countries, with each location contributing to Proofpoint’s amazing culture!  #LI-AN1

If you like wild growth and working with happy, enthusiastic over-achievers, you'll enjoy your career with us!

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* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰

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Tags: AWS BERT CI/CD Data pipelines EC2 ETL Excel GPT Lambda LLMs Machine Learning ML models MLOps Pipelines PySpark Python PyTorch SageMaker Scrum Security TensorFlow

Perks/benefits: Career development Team events

Region: South America
Country: Argentina

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