Responsibilities
- Define AI infrastructure strategy and architect scalable compute, storage, and networking solutions for the full AI lifecycle.
- Lead and mentor infrastructure engineers, establish engineering standards, and conduct design reviews.
- Design and own platforms and processes for deploying, monitoring, and managing AI models in production, including model serving, A/B testing, and rollback mechanisms.
- Architect automation pipelines for AI model training, evaluation, testing, and deployment, including infrastructure-as-code and CI/CD improvement.
- Partner with data scientists, ML engineers, product managers, and leadership to align infrastructure with research and business objectives.
- Profile, benchmark, and optimize AI infrastructure and model serving for throughput, latency, GPU utilization, scalability, and cost.
- Establish security, access control, compliance, and governance practices across AI infrastructure.
- Own capacity forecasting, resource planning, and cost optimization for GPU clusters and related infrastructure.
Requirements
- Bachelor’s or master’s degree in computer engineering, electrical engineering, computer science, or a related field; an advanced degree is preferred.
- 12+ years of experience in software engineering, infrastructure engineering, DevOps/SRE, or a related field, including at least four years focused on AI/ML infrastructure.
- Experience leading or mentoring engineering teams on infrastructure projects.
- Deep expertise in computer systems, distributed systems, and cloud computing architectures.
- Strong proficiency in Python and at least one additional systems language such as Go, C++, Rust, or Java.
- Expert-level Linux system administration, including package management, user and group management, file systems, shell scripting, networking, system configuration, and kernel tuning.
- Strong architectural judgment across performance, reliability, security, and cost, along with excellent communication and collaboration skills.
- Expertise with observability stacks and model monitoring, including Prometheus, Grafana, ELK/OpenSearch, Datadog, OpenTelemetry, and open inference.
- Experience with AI/ML frameworks, major cloud platforms, hybrid cloud architectures, Docker, Kubernetes, infrastructure-as-code tools, and LLM training or inference infrastructure is preferred.
Benefits
- Hybrid working model with a 3:2 schedule.
- Holiday purchase, private medical coverage, income protection, pension scheme, life insurance, and positive work-life balance.
- Learning and development opportunities.
- Lenovo and Motorola product discounts, lifestyle discounts, cycle-to-work benefits, MyGymDiscounts, mortgage advice and support, and referral bonus.
Tech Stack
Categories
About Lenovo
Lenovo is a US$83 billion revenue global technology powerhouse, ranked #196 in the Fortune Global 500, and serving millions of customers every day in 180 markets. Guided by its vision of “Smarter Technology for All”, Lenovo is executing a Hybrid AI strategy that spans Personal AI – one personal AI, multiple devices; and Enterprise AI – helping customers turn data into insights and value. This strategy is delivered through the Group’s commitment to world-class innovation and a full-stack AI portfolio, including devices (PCs, workstations, smartphones, tablets, accessories), infrastructure solutions (server, storage, edge, high performance computing and software defined infrastructure), as well as software, solutions, and services. With a global footprint spanning 21 research and development locations in 11 markets, and a global supply chain including more than 30 manufacturing sites across 10 markets, Lenovo is widely recognized for its operational excellence, including ranking #8 in the Gartner Supply Chain Top 25. Lenovo is listed on the Hong Kong stock exchange under Lenovo Group Limited (HKSE: 992) (ADR: LNVGY). To find out more visit https://www.lenovo.com, and read about the latest news via our StoryHub at https://news.lenovo.com/. To learn more about our career opportunities, visit our careers page at http://jobs.lenovo.com/.