Join to apply for the Sr. Machine Learning Engineer (Remote) role at CrowdStrike Continue with Google Continue with Google Join to apply for the Sr. Machine Learning Engineer (Remote) role at CrowdStrike As a global leader in cybersecurity, CrowdStrike protects the people, processes and technologies that drive modern organizations. Since 2011, our mission hasn’t changed — we’re here to stop breaches, and we’ve redefined modern security with the world’s most advanced AI-native platform. Our customers span all industries, and they count on CrowdStrike to keep their businesses running, their communities safe and their lives moving forward. We’re also a mission-driven company. We cultivate a culture that gives every CrowdStriker both the flexibility and autonomy to own their careers. We’re always looking to add talented CrowdStrikers to the team who have limitless passion, a relentless focus on innovation and a fanatical commitment to our customers, our community and each other. Ready to join a mission that matters? The future of cybersecurity starts with you. About The Role Crowdstrike’s Data Science team is expanding – we are looking for a Senior Machine Learning Engineer to join our growing Data Science organization. You will build scalable and resilient systems which help train, evaluate, and integrate some of the largest and most complex machine learning models in the industry. You will also have the opportunity to apply your expertise in software engineering and knowledge of ML to accelerate scientific research in areas such as: algorithm optimization, algorithm scaling, and modeling automation. The scale of our systems and data are approaching Exabytes in size. Experience with extremely large-scale systems, including DevOps patterns, practices, and standards are important for this work. What You’ll Do Apply deep knowledge of distributed systems to improving existing and new model training systems and scale novel data processing techniques Apply machine learning knowledge to quickly understand and build automated systems that encapsulate manual ML research workflows Champion proper engineering and architectural approaches to ML workflows with scientists, engineers, analysts, architects and management Productionize research projects by optimizing code and systems to perform within various engineering performance envelopes Employ and evolve established CrowdStrike tools and services to build solutions for detecting and countering targeted cyber assaults. Apply software engineering best practices to machine learning code bases and systems to improve reliability and observability Automate and visualize analyses, results and processes in our artificial intelligence and machine learning pipeline Own your work with autonomy, end to end: develop, test, deploy and monitor your changes Tech Stack (not mandatory to know everything; a robust learning capacity is essential): Python (xgboost, pytorch, tensorflow, scikit-learn, pandas, huggingface) Docker Kubernetes
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