Senior AI Infrastructure Engineer, LLM/AI Platforms

🕒 July 7

🇺🇸 United States – Remote

💵 $140k - $215k / year

⏰ Full Time

🟠 Senior

👷 Infrastructure Engineer

🦅 H1B Visa Sponsor

This company has sponsored H1B visas in the past.

👻 Ghost score 5%

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CrowdStrike

WebsiteLinkedInAll Job Openings

5001 - 10000 employees

Founded 2011

🔒 Cybersecurity

☁️ SaaS

🤖 Artificial Intelligence

Cybersecurity • SaaS • Artificial Intelligence

CrowdStrike is a cybersecurity company that provides cloud-based security services to stop breaches. It is recognized as a leader in endpoint protection, identity and cloud security, and managed detection and response. CrowdStrike's platform, Falcon, integrates artificial intelligence to offer real-time visibility, detection, and protection against sophisticated cyber threats. The company is lauded for its effectiveness in securing networks and data, making it a trusted partner for businesses worldwide.

📋 Description

• Provision and configure large GPU clusters and compute resources for LLM training, finetuning, and inference workloads. • Develop and optimize LLM model-serving infrastructure, including deployment and optimization of various inference frameworks. • Lead model lifecycle management including versioning, checkpointing and reproducibility across training and inference deployments. • Design and champion robust evaluation frameworks to assess model performance, accuracy, and reliability, ensuring AI systems are consistently at production-ready standards. • Identify and address GPU utilization and GPU memory efficiency bottlenecks and apply techniques like quantization, batching, and caching. • Architect and maintain data platforms and pipelines specifically designed to support LLMs, Retrieval-Augmented Generation (RAG), and AI Agentic Systems at scale. • Deliver production-ready code with a focus on performance, maintainability, and testing rigor, ensuring the ability to ship fast without compromising quality. • Apply expertise in data modeling, normalization, and semantic cataloging for AI/ML workloads. • Define and enforce best practices for MLOps/DataOps surrounding LLMs, including monitoring, observability, and zero-touch recovery mechanisms for AI services. • Document architectural designs thoroughly and communicate technical decisions clearly to stakeholders. • Collaborate across the organization with Data Scientists, Product Managers, and other engineering teams to transform research prototypes into robust, production-grade services.

🎯 Requirements

• Bachelor’s degree in Computer Science, Data Engineering, or a related STEM field; Master’s degree preferred • 6+ years of experience in Infrastructure/Data Engineering, with at least 2 years focused on building and maintaining platforms/pipelines that support LLM-based systems and applications • Demonstrable hands-on experience in LLM infrastructure engineering including cluster provisioning, optimizing training workloads, and maintaining inference pipelines • Exceptional ability to write clean, elegant, performant, and well-tested code, coupled with a strong focus on action and delivering results quickly • Thorough understanding of engineering practices including effective peer code reviews and resilient architecture design • Demonstrates technical leadership and mentorship capabilities • Proven experience utilizing AI technologies to enhance decision-making, streamline workflows and processes, improve efficiency and drive business outcomes.

🏖️ Benefits

• 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