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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.
The Role We're seeking a Senior 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.
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