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CrowdStrike is seeking a talented MLOps Engineer to contribute to its mission as a global leader in cybersecurity. The company is committed to protecting the people, processes, and technologies that drive modern organizations, redefining security with its AI-native platform since its inception. With a strong emphasis on innovation and employee autonomy, CrowdStrike fosters a culture that allows individuals to grow in their careers while supporting their customers and community.
As an MLOps Engineer at CrowdStrike, you will play a pivotal role in their Machine Learning Platform Engineering initiatives. This position involves designing and building globally distributed, fault-tolerant systems that enhance the cybersecurity capabilities of the organization. You’ll collaborate with various teams to deliver high-impact solutions while participating in a supportive work culture that emphasizes continuous learning.
The primary responsibilities of the MLOps Engineer include:
Design and implement CI/CD pipelines and automation processes to streamline development workflows.
Collaborate with data scientists to seamlessly integrate CI/CD into the development lifecycle.
Identify and execute opportunities for process automation and optimization.
Implement and enforce security measures across repositories.
Innovate with cutting-edge machine learning technologies to power data science initiatives.
Focus on building scalable and cost-effective solutions.
Set up alerts and dashboards to proactively manage performance and reliability issues.
Conduct in-depth monitoring, analysis, and identification of vulnerabilities or gaps in existing systems.
Utilize established CrowdStrike tools and services for identifying and mitigating cyber threats.
Collaborate across teams to devise innovative solutions, emphasizing high coding standards and continuous improvement.
Mentor fellow engineers, sharing knowledge and best practices while also learning from them.
Candidates should possess the following skills:
STEM degree (undergraduate) in a related field.
Experience with big data and microservices environments.
A solid understanding of scalability concepts and distributed systems, including sharding, partitioning, and concurrency.
Familiarity with engineering best practices, including robust testing paradigms, effective peer code reviews, and resilient architecture principles.
Ability to thrive in a test-driven and collaborative programming environment.
Skills in delivering high-quality software that is regularly tested and integrated for continuous development.
While familiarity with the following technologies isn’t mandatory, a willingness and capability to learn are essential:
ML Model Deployment tools such as MLFlow, Kubeflow, Triton, or Databricks.
Distributed Systems proficiencies, such as Kafka, Cassandra, or Spark.
High-level programming languages, like Python or JVM technologies.
Knowledge of container technologies, including Docker and Kubernetes.
Understanding of infrastructure as code solutions (e.g., Terraform, Chef).
CrowdStrike offers a comprehensive set of benefits designed to support employee wellness and professional development, including:
The base salary range for the MLOps Engineer position in the U.S. is between $135,000 and $215,000 annually, alongside variable or incentive compensation, equity options, and benefits. Salary offers consider various factors, including relevant experience, skills, certifications, job level, and location, ensuring a fair and competitive compensation package.
CrowdStrike is dedicated to fostering an inclusive workplace where all employees can thrive. The company is committed to diversity, ensuring equal opportunity in all employment practices regardless of race, ethnicity, gender, age, or disability. By joining as an MLOps Engineer, you will be stepping into a dynamic and impactful role in the ever-evolving field of cybersecurity, where your contributions will significantly affect business outcomes and community safety.
This job offer was originally published on himalayas.app
This job offer summary has been generated using automated technology. While we strive for accuracy, it may not always fully capture the nuances and details of the original job posting. We recommend reviewing the complete job listing before making any decisions or applications.