Machine Learning Engineer II (Remote)
About the Company
CrowdStrike is a global cybersecurity company focused on preventing security breaches through advanced technology, artificial intelligence, and threat intelligence. Founded in 2011, the company developed its Falcon platform to help organizations detect and stop sophisticated attacks. Its platform processes nearly 3 trillion events per day, supporting customers across a wide range of industries. CrowdStrike promotes flexibility, autonomy, continuous learning, and responsible AI adoption. The company encourages employees to use AI to improve execution, uncover insights, and solve complex technical challenges while maintaining a strong focus on customer needs.
About the Role
CrowdStrike is seeking a Senior Machine Learning Engineer to join its AIDR Engineering Team. In this role, you will provide engineering support to a data science group working on high-throughput, low-latency large language model (LLM) inference. You will collaborate closely with engineers and applied data scientists on LLM post-training, data engineering, model evaluation, and the development of scalable AI applications. The team focuses on helping enterprise users interact with AI applications safely and securely. You will contribute to the infrastructure, data pipelines, and custom models that support this work, helping research and development teams turn new ideas into reliable, customer-facing solutions. This position requires strong engineering fundamentals, an understanding of modern machine learning systems, and the ability to work effectively with fast-moving research teams. Previous cybersecurity experience is not required. CrowdStrike will provide mentoring and training in security-related topics as needed.
Key Responsibilities
Develop engineering solutions that help data science teams work with advanced machine learning technologies and accelerate research. Support LLM post-training, model development, and data engineering activities aligned with rigorous evaluation practices. Build, maintain, and improve data pipelines that support advanced data science use cases. Contribute to the training, implementation, and deployment of custom machine learning models. Develop high-quality software for customer-facing applications operating at scale. Analyze systems and identify potential vulnerabilities, technical gaps, and opportunities for improvement. Collaborate with engineers, applied data scientists, and product teams to define problems and develop practical solutions. Apply engineering best practices, including rigorous testing, peer code reviews, logging, and performance metrics. Develop, test, deploy, and monitor changes throughout the software development lifecycle. Improve product architecture, knowledge models, user experience, performance, and reliability. Explore ways to scale low-latency inference across GPUs and GPU clusters. Use AI technologies to improve decision-making, streamline workflows, increase efficiency, and support business outcomes. Contribute to technical discussions and mentor fellow engineers while continuing to learn from colleagues across different disciplines. Stay informed about customer challenges and help improve the reliability and effectiveness of AI-powered products.
Required Qualifications
Previous experience in data engineering and architecture supporting advanced data science applications. Deep understanding of LLM post-training methods and the computational architectures used to support them. Understanding of scalable and distributed systems, including sharding, partitioning, and concurrency. Strong programming skills in Python or high-level programming languages, including JVM technologies. Knowledge of software engineering best practices, including appropriate testing methods, peer code reviews, and resilient architecture. Experience working in test-driven, collaborative, and iterative development environments. Ability to deliver high-quality, unit-tested, code-reviewed software and contribute regularly to continuous integration workflows. Demonstrated experience using AI technologies to improve decision-making, streamline workflows and processes, increase efficiency, or drive business outcomes. Strong collaboration skills and the ability to work effectively with engineers, data scientists, and product teams. Commitment to continuous learning, accountability, and delivering reliable software. Technical Environment The team's technology stack includes the following tools and platforms. Candidates are not expected to know every technology but should demonstrate the ability to learn and adapt. Programming: Python and JVM technologies. Containers and orchestration: Docker and Kubernetes. Cloud platforms: AWS, Google Cloud Platform (GCP), and MaaS. Data processing and distributed systems: Kafka, Cassandra, and Spark. Search: Elasticsearch. Infrastructure automation: Terraform, Chef, and Ansible. Machine learning infrastructure: GPU and GPU-cluster inference scaling.
Preferred Qualifications
Demonstrable applied experience building scalable architectures for LLM post-training or fine-tuning. Previous experience in cybersecurity or intelligence-related fields. Experience scaling machine learning inference across GPUs or GPU clusters. Location and Work Arrangement Location: United States. Work arrangement: Remote. Salary and Benefits Base salary: $140,000–$215,000 per year for U.S. candidates. Additional compensation may include bonuses and equity grants. Health insurance, a 401(k) plan, and paid time off. Physical and mental wellness programs. Competitive vacation and holiday allowances. Paid parental and adoption leave. Professional development opportunities across all employee levels and roles. Employee networks, geographic neighborhood groups, and volunteer opportunities. Access to office amenities and opportunities to connect with colleagues. Final compensation depends on factors such as relevant work experience, skills, certifications, job level, supervisory status, and location. Equal Employment Opportunity CrowdStrike is an equal opportunity employer committed to creating an inclusive workplace where employees are valued and supported. Employment decisions are based on valid job requirements, without discrimination based on race, color, creed, ethnicity, religion, sex, pregnancy or related medical conditions, sexual orientation, gender identity, marital or family status, veteran status, age, national origin, ancestry, physical or mental disability, medical condition, genetic information, membership or activity in a local human rights commission, public assistance status, or any other characteristic protected by applicable law. The company supports veterans and individuals with disabilities through its affirmative action program. CrowdStrike participates in the E-Verify program and provides assistance with website accessibility, applications, and accommodation requests through [email protected].