Sr ML Platform Engineer Hybrid

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. We work on large scale distributed systems, processing almost 3 trillion events per day and this traffic is growing daily. 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:

Were seeking a Sr. Engineer - ML Platform to maintain and optimize CrowdStrikes mission-critical ML infrastructure. Youll diagnose complex distributed systems issues and ensure platform reliability for infrastructure processing billions of events daily.

What Youll Do:

Platform Reliability & Debugging: Diagnose and resolve issues across Ray, Spark, Airflow, MLflow, JupyterHub, Kubeflow, and SLURM Perform root cause analysis on production incidents affecting training and inference pipelines Debug performance bottlenecks, resource contention, memory leaks, and scheduling conflicts Develop debugging tools and diagnostic frameworks

System Optimization & Performance: Profile and optimize Ray clusters and Spark jobs on K8s and Cloud (EMR/Dataproc) Troubleshoot JupyterHub spawner issues, kernel crashes, and resource allocation Optimize SLURM job scheduling, GPU allocation, and HPC cluster utilization

Infrastructure & Monitoring: Build observability solutions and automated health checks Develop runbooks, alerting workflows, and incident response procedures Maintain platform stability metrics (SLAs, error rates, latency)

Collaboration: Partner with ML and ML Platform engineers to resolve workflow issues Conduct post-mortems and mentor on debugging techniques

What Youll Need:

• 12+ years in distributed systems engineering
• 5+ years debugging ML platforms in production
• Deep expertise in 3+ one of: Ray, Spark, JupyterHub, SLURM, K8 Performance profiling, optimization, and capacity planning
  
  

Technical Skills (Expertise In At Least One):

• Distributed ML: Ray, Spark, SLURM, Jupyter Ecosystem (debugging failures, performance tuning)
• ML Platforms: Airflow, MLflow, JupyterHub (troubleshooting core components) Infrastructure: Kubernetes, Docker, AWS/GCP/Azure/OCI
• Observability: Profiling tools, distributed tracing, Prometheus, Grafana, log aggregation
• Programming: Expert Python debugging, multi-language proficiency, Linux/Unix
  
  

What Sets You Apart: Open-source ML infrastructure contributions Experience with high-throughput inference systems and reducing MTTR Published debugging guides or tools Chaos engineering and GPU/CUDA debugging experience On-call and incident management experience

Benefits Of Working At CrowdStrike:

• Market leader in compensation and equity awards
• Comprehensive physical and mental wellness programs
• Competitive vacation and holidays for recharge
• Paid parental and adoption leaves
• Professional development opportunities for all employees regardless of level or role
• Employee Networks, geographic neighborhood groups, and volunteer opportunities to build connections
• Vibrant office culture with world class amenities
• Great Place to Work Certified™ across the globe
  
  

CrowdStrike is proud to be an equal opportunity employer. We are committed to fostering a culture of belonging where everyone is valued for who they are and empowered to succeed. We support veterans and individuals with disabilities through our affirmative action program.

CrowdStrike is committed to providing equal employment opportunity for all employees and applicants for employment. The Company does not discriminate in employment opportunities or practices on the basis of race, color, creed, ethnicity, religion, sex (including pregnancy or pregnancy-related medical conditions), sexual orientation, gender identity, marital or family status, veteran status, age, national origin, ancestry, physical disability (including HIV and AIDS), mental disability, medical condition, genetic information, membership or activity in a local human rights commission, status with regard to public assistance, or any other characteristic protected by law. We base all employment decisions--including recruitment, selection, training, compensation, benefits, discipline, promotions, transfers, lay-offs, return from lay-off, terminations and social/recreational programs--on valid job requirements.

If you need assistance accessing or reviewing the information on this website or need help submitting an application for employment or requesting an accommodation, please contact us at recruiting@crowdstrike.com for further assistance.

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Technical Skills (Expertise In At Least One):

• Distributed ML: Ray, Spark, SLURM, Jupyter Ecosystem (debugging failures, performance tuning)
• ML Platforms: Airflow, MLflow, JupyterHub (troubleshooting core components) Infrastructure: Kubernetes, Docker, AWS/GCP/Azure/OCI
• Observability: Profiling tools, distributed tracing, Prometheus, Grafana, log aggregation
• Programming: Expert Python debugging, multi-language proficiency, Linux/Unix
  
  

What Sets You Apart: Open-source ML infrastructure contributions Experience with high-throughput inference systems and reducing MTTR Published debugging guides or tools Chaos engineering and GPU/CUDA debugging experience On-call and incident management experience

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