Sr. Machine Learning Engineer

CrowdStrike is seeking a Sr. Machine Learning Engineer to join the AIDR Engineering Team. The team’s mission includes engineering support for high-throughput, low-latency LLM inferencing, with a focus on post-training work, data engineering grounded in rigorous evaluations, and building enterprise-grade interactions that prioritize safety and security.

This role blends hands-on ML and systems engineering with collaboration across teams to turn research into reliable, scalable solutions for customer-facing applications. You will work end to end, from development and testing through deployment and monitoring.

Key Responsibilities

• Drive innovation using state-of-the-art machine learning approaches to help accelerate data science.
• Provide pragmatic engineering support to keep fast-moving research and development efforts progressing.
• Implement high-quality solutions that support customer-facing applications at scale.
• Perform in-depth analysis to identify potential vulnerabilities or gaps.
• Construct and maintain data pipelines, and contribute to training and implementation of custom models.
• Collaborate with cross-functional teams to brainstorm, define, and devise solutions.
• Commit to ongoing learning and continuous self-improvement.
• Stay close to customer challenges and work to enhance engineering support.
• Maintain top-tier coding quality through best practices, rigorous testing, and thorough logging and metrics.
• Work effectively in a collaborative, agile team environment.
• Contribute to mentoring engineers across a spectrum of technologies, while also learning from them.
• Explore ways to refine product architecture, knowledge models, user experience, performance, and reliability.
• Own work with autonomy end to end: develop, test, deploy, and monitor changes.
• Thrive in an environment that places a high value on trust.

Qualifications

• Prior experience with data engineering and architecture supporting advanced data science use cases.
• Deep understanding of LLM post-training methods and computational architectures.
• Knowledge of scalability and distributed systems, including sharding, partitioning, and concurrency.
• Ability to work as a team player.
• Strong grasp of engineering best practices, including testing paradigms, peer code reviews, and resilient architecture.
• Capacity to succeed in a test-driven, collaborative, iterative development environment.
• Track record of delivering high-quality, unit-tested software through regular code reviews and continuous integration.
• Proven experience using AI technologies to improve decision-making, streamline workflows, increase efficiency, and deliver measurable business outcomes.

Technologies and Tools

Note: The role lists a broad set of technologies to support the work.

• Python, JVM technologies
• Docker, Kubernetes
• AWS, GCP, MaaS
• MaaS, Kafka, Cassandra, Spark
• ElasticSearch
• Terraform, Chef, Ansible
• GPUs, including scaling inference across GPUs or GPU clusters

Bonus Points

• Demonstrable applied experience building scalable architectures for LLM post-training or fine-tuning.
• Prior experience in cybersecurity or intelligence fields.

Compensation and Location

• Location: Sunnyvale, CA (remote)
• Salary: USD 164,000 - 295,000 per year

Benefits

• Market-leading compensation and equity awards
• Comprehensive physical and mental wellness programs
• Competitive vacation and holidays
• Paid parental and adoption leaves
• Professional development opportunities for all employees
• Employee Networks, geographic neighborhood groups, and volunteer opportunities
• Vibrant office culture with world-class amenities
• Great Place to Work Certified™ across the globe