About the Company

CrowdStrike is a global cybersecurity company founded in 2011. Its AI-native security platform helps organizations protect their systems, data, and operations against cyber threats. The company processes nearly 3 trillion events per day and focuses on preventing security breaches through advanced technology and threat intelligence.

About the Role

CrowdStrike is seeking a Senior Machine Learning Engineer to join its AIDR Engineering team. This fully remote, US-based position focuses on supporting data science initiatives involving high-throughput, low-latency large language model (LLM) inference, post-training, and evaluation-driven data engineering. You will work closely with engineers and applied data scientists to develop scalable AI solutions that help enterprise users interact with AI applications safely and securely. The role involves building production-ready systems, improving model performance, maintaining reliable data pipelines, and taking ownership of engineering changes from development through deployment and monitoring. Previous cybersecurity industry experience is not required, but an interest in CrowdStrike's mission and customer needs is expected.

Key Responsibilities

Apply advanced machine learning technologies to accelerate data science research and development. Build high-quality engineering solutions for customer-facing applications operating at scale. Support LLM post-training and data engineering processes aligned with rigorous model evaluation. Develop and maintain data pipelines and contribute to training and implementing custom models. Analyze systems to identify potential vulnerabilities, weaknesses, and performance gaps. Collaborate with engineers, applied data scientists, and cross-functional teams to define and implement solutions. Maintain high coding standards through rigorous testing, effective logging, metrics, and engineering best practices. Participate in peer code reviews and follow appropriate testing and continuous integration practices. Develop, test, deploy, and monitor changes throughout the software lifecycle. Improve product architecture, knowledge models, user experience, performance, and reliability. Contribute to mentoring engineers while continuing to learn from colleagues across different technical areas. Use AI technologies to improve decision-making, streamline workflows, and support business outcomes. Maintain a customer-focused approach by identifying opportunities to improve products and support.

Required Qualifications

Experience in data engineering and architecture supporting advanced data science applications. Strong understanding of LLM post-training methods and computational architectures. Understanding of scalable and distributed systems, including sharding, partitioning, and concurrency. Knowledge of software engineering best practices, including testing methodologies, peer code reviews, and resilient architecture. Ability to work in a test-driven, collaborative, and iterative development environment. Experience delivering high-quality, unit-tested, reviewed code that supports continuous integration. Demonstrated ability to meet commitments and deliver reliable software on schedule. Experience using AI technologies to improve decision-making, streamline workflows, increase efficiency, and drive business outcomes. Strong teamwork skills and a commitment to continuous learning. Technical Environment The team works with technologies across several areas, including: High-level programming languages, such as Python and JVM technologies. Docker and Kubernetes. Cloud platforms, including AWS, GCP, or MaaS. Kafka, Cassandra, and Spark. Elasticsearch. Infrastructure automation tools, including Terraform, Chef, and Ansible. GPU and GPU-cluster inference scaling. Candidates are not expected to know every technology listed but should demonstrate strong technical learning ability.

Preferred Qualifications

Demonstrable applied experience with scalable architectures for LLM post-training or fine-tuning. Previous experience in cybersecurity or intelligence-related fields. Experience scaling inference workloads across GPUs or GPU clusters.

Compensation and Benefits

Base Salary: $140,000–$215,000 per year for US candidates. Additional compensation may include bonuses and equity grants. Health insurance, 401(k), and paid time off. Physical and mental wellness programs. Paid parental and adoption leave. Competitive vacation and holiday allowances. Professional development opportunities. Employee networks, geographic community groups, and volunteer opportunities. Compensation depends on factors including relevant experience, skills, certifications, job level, supervisory status, and location. Equal Employment Opportunity CrowdStrike is an equal opportunity employer committed to fostering an inclusive workplace. Employment decisions are based on valid job requirements, without discrimination on the basis of characteristics protected by applicable law. The company supports veterans and individuals with disabilities through its affirmative action program. CrowdStrike participates in the E-Verify program. Applicants who need assistance with the application process or workplace accommodations can contact recruiting@crowdstrike.com. Employment Details Job Title: Senior Machine Learning Engineer Company: CrowdStrike Location: United States Work Arrangement: Remote Employment Type: Full-time