Descrizione dell'offerta
Experteer Overview
As principal architect, you define the vision for compute infrastructure that underpins large-scale AI/ML systems. You guide the architecture across compute, networking, storage, and orchestration to deliver scalable, cost-aware production systems. You work with cross-functional teams, validate designs with prototypes and benchmarks, and mentor others while driving strategic roadmaps. Your deep hyperscaler expertise informs decisions that balance performance, cost, and business value, shaping the firm of AI infrastructure trajectory. Benefits
Set and communicate the overarching compute infrastructure strategy for AI/ML systems Make authoritative architecture decisions across compute, networking, storage, orchestration, and model serving Architect and prototype large-scale, cost-optimized compute and distributed training systems with reference implementations and benchmarks Define reference architectures, standards, and patterns and implement foundational tooling and automation Lead enterprise-scale architecture assessments and design reviews with hands‑on validation Shape the AI infrastructure roadmap and plan capacity and technology evolution Identify and pilot emerging technologies with real-condition testing Drive performance and cost optimization of GPU/compute workloads to meet SLAs Serve as the principal authority on hyperscaler cloud platforms with hands‑on AI/ML expertise Lead root‑cause analysis for complex issues across hardware, network, software, and models Foster relationships with infrastructure partners for early access and credibility Provide executive‑ and client‑level advisory translating trade‑offs into business outcomes Define monitoring, observability, reliability strategies and implement SLAs, SLOs and governance for production AI/ML systems Ensure security, compliance, and regulatory alignment across AI/ML infrastructure Mentor and develop the architect community to deliver impact Champion cost‑efficiency and value realization across the stack Responsibilities
Significant experience coding, building, monitoring and troubleshooting AI/ML applications and deploying them on premises or public cloud Strong understanding of AI/ML concepts Strong understanding of computing infrastructure; knowledge of AI infrastructure preferred Proficiency in Python, Java, or C++ Experience with data pipelines/workflow tools (e.g., Apache Airflow, Kubeflow) Strong problem‑solving ability and fast‑paced adaptability Excellent communication and collaboration skills Extensive experience in AI/ML infrastructure engineering on hyperscaler platforms for large‑scale deployments Proven leadership and management of AI projects and teams Strong project management skills with multi‑project capability Experience evaluating and selecting AI technologies and frameworks Ability to collaborate with cross‑functional teams and drive project alignment
#J-18808-Ljbffr
As principal architect, you define the vision for compute infrastructure that underpins large-scale AI/ML systems. You guide the architecture across compute, networking, storage, and orchestration to deliver scalable, cost-aware production systems. You work with cross-functional teams, validate designs with prototypes and benchmarks, and mentor others while driving strategic roadmaps. Your deep hyperscaler expertise informs decisions that balance performance, cost, and business value, shaping the firm of AI infrastructure trajectory. Benefits
Set and communicate the overarching compute infrastructure strategy for AI/ML systems Make authoritative architecture decisions across compute, networking, storage, orchestration, and model serving Architect and prototype large-scale, cost-optimized compute and distributed training systems with reference implementations and benchmarks Define reference architectures, standards, and patterns and implement foundational tooling and automation Lead enterprise-scale architecture assessments and design reviews with hands‑on validation Shape the AI infrastructure roadmap and plan capacity and technology evolution Identify and pilot emerging technologies with real-condition testing Drive performance and cost optimization of GPU/compute workloads to meet SLAs Serve as the principal authority on hyperscaler cloud platforms with hands‑on AI/ML expertise Lead root‑cause analysis for complex issues across hardware, network, software, and models Foster relationships with infrastructure partners for early access and credibility Provide executive‑ and client‑level advisory translating trade‑offs into business outcomes Define monitoring, observability, reliability strategies and implement SLAs, SLOs and governance for production AI/ML systems Ensure security, compliance, and regulatory alignment across AI/ML infrastructure Mentor and develop the architect community to deliver impact Champion cost‑efficiency and value realization across the stack Responsibilities
Significant experience coding, building, monitoring and troubleshooting AI/ML applications and deploying them on premises or public cloud Strong understanding of AI/ML concepts Strong understanding of computing infrastructure; knowledge of AI infrastructure preferred Proficiency in Python, Java, or C++ Experience with data pipelines/workflow tools (e.g., Apache Airflow, Kubeflow) Strong problem‑solving ability and fast‑paced adaptability Excellent communication and collaboration skills Extensive experience in AI/ML infrastructure engineering on hyperscaler platforms for large‑scale deployments Proven leadership and management of AI projects and teams Strong project management skills with multi‑project capability Experience evaluating and selecting AI technologies and frameworks Ability to collaborate with cross‑functional teams and drive project alignment
#J-18808-Ljbffr
Candidatura e Ritorno (in fondo)
Ricevi annunci simili
Inserisci la tua email: ti avvisiamo quando escono nuovi annunci corrispondenti.
✅ Controlla la tua email e clicca il link per confermare l'alert.
Nessun account necessario. Disiscrizione con un clic dall'email.