AI Infra Advisory Researcher

The Advisory Researcher in AI Compute and Data Infrastructure will provide senior technical leadership for the research, architecture, and development of intelligent, high-performance, and resilient Hybrid AI systems. This position combines research depth, hands-on software development, system architecture expertise, and the ability to translate emerging technologies into production infrastructure and differentiated product capabilities., * Define technical directions and lead major research and development initiatives in AI compute and data infrastructure, distributed AI systems, and intelligent infrastructure management.

• Identify high-impact technical opportunities based on infrastructure challenges, emerging technologies, product requirements, and business value.
• Architect end-to-end AI infrastructure solutions spanning hardware, system software, data platforms, distributed training and inference, and application workloads.
• Lead hardware/software co-analysis and co-optimization across GPUs, accelerators, CPUs, memory hierarchy, storage, networking, runtimes, frameworks, and AI applications.
• Define optimization strategies for GPU utilization, workload placement, resource orchestration, memory and cache efficiency, communication, data movement, storage access, and model execution.
• Lead the architecture and optimization of large-scale data pipelines for data ingestion, preprocessing, transformation, storage, retrieval, and delivery to AI workloads.
• Define intelligent observability and diagnostic technologies for anomaly detection, root-cause analysis, performance regression, capacity planning, system health assessment, and predictive maintenance.
• Develop resilient and fault-tolerant infrastructure architectures, including failure isolation, checkpointing and recovery, redundancy, retry, failover, graceful degradation, and automated remediation.
• Apply machine learning and deep learning to system modeling, infrastructure control, workload forecasting, resource optimization, failure prediction, and operational intelligence.
• Apply time-series modeling and signal processing to telemetry analytics, event detection, change-point detection, capacity forecasting, and system health monitoring.
• Apply causal inference and causal discovery to root-cause analysis, performance attribution, intervention evaluation, and automated decision-making.
• Define knowledge graph architectures for modeling infrastructure topology, hardware/software dependencies, workloads, operational events, and failure relationships.
• Make architecture-level trade-offs involving performance, scalability, reliability, availability, energy consumption, cost, security, and maintainability.
• Lead technical design reviews, architecture reviews, performance investigations, and resolution of complex cross-layer system issues.
• Provide hands-on technical guidance in algorithm design, software implementation, system optimization, experimental validation, and production deployment.
• Establish reusable frameworks, engineering practices, evaluation methodologies, and technical standards for AI infrastructure development.
• Partner with research, engineering, architecture, product, and business teams to transition research into Enterprise AI and Personal AI platforms and products.
• Mentor Staff Researchers and engineers and contribute to patents, publications, technical standards, and differentiated intellectual property.

This candidate MUST be a US citizen or US national; US permanent residents or candidates requiring sponsorship cannot be considered., * Master’s or PhD degree in computer science, computer engineering, artificial intelligence, electrical engineering, applied mathematics, or a related field, or equivalent practical experience.

• Seven or more years of relevant experience in AI compute and data infrastructure, machine learning systems, distributed systems, data platforms, performance engineering, reliability engineering, or advanced software development.
• Demonstrated leadership of technically complex research, architecture, or system development initiatives.
• Strong hands-on programming and system architecture capabilities.
• Deep expertise in at least three of the following areas:
• Machine learning or deep learning
• GPU or accelerator optimization
• Distributed AI training and inference
• Large-scale and streaming data processing
• Hardware/software co-optimization
• Time-series modeling or signal processing
• Infrastructure diagnostics, reliability, and fault tolerance
• Causal inference
• Knowledge graphs or graph-based reasoning
• Proven record of delivering advanced software, infrastructure, or research technologies into products or production environments.
• Ability to resolve ambiguous, cross-layer technical problems and make informed architecture-level trade-offs.
• Strong technical communication, mentorship, and cross-organizational influence., * Experience architecting enterprise-scale cloud, edge, on-premises, or hybrid AI infrastructure.
• Experience with PyTorch, TensorFlow, JAX, CUDA, ROCm, Spark, Flink, Ray, Kafka, Kubernetes, or related technologies.
• Experience with MLOps, observability platforms, distributed computing, data lakehouse architectures, or cloud-native systems.
• Strong publication record, patent portfolio, open-source contributions, or demonstrated commercial product impact.

Why Work at Lenovo We are Lenovo. We do what we say. We own what we do. We WOW our customers. Lenovo is a US$83 billion revenue global technology powerhouse, ranked #153 in the Fortune Global 500, and serving millions of customers every day in 180 markets. Focused on a bold vision to deliver Smarter Technology for All, Lenovo has built on its success as the world’s largest PC company with a full-stack portfolio of AI-enabled, AI-ready, and AI-optimized devices (PCs, workstations, smartphones, tablets), infrastructure (server, storage, edge, high performance computing and software defined infrastructure), software, solutions, and services. Lenovo’s continued investment in world-changing innovation is building a more equitable, trustworthy, and smarter future for everyone, everywhere. Lenovo is listed on the Hong Kong stock exchange under Lenovo Group Limited (HKSE: 992) (ADR: LNVGY). This transformation together with Lenovo’s world-changing innovation is building a more inclusive, trustworthy, and smarter future for everyone, everywhere. To find out more visit www.lenovo.com, and read about the latest news via our StoryHub.