Cisco Technical Marketing Engineer 

India, Karnataka, Bengaluru 

471397230

Role also includes the following:

• Conduct performance tests on UCS hardware and software (CPUs, GPUs, memory, networking, storage)
• Build performance benchmarks, analyse results, and develop technical marketing materials (white papers, standard process guides, presentations)
• Use industry-standard benchmarking tools (e.g., SPEC, vdbench) to evaluate system performance
• Provide technical guidance to improve UCS performance for specific customer environments
• Solve Cisco UCS performance issues
• Collaborate with engineering, product management, and sales teams to ensure industry-leading UCS performance
• Support Cisco Technical Support post-sales for performance debugging and optimizations
• Must be a self-starter and a teammate.
• Ability to set and meet timelines,

Who You Are:

You are 9+ years of experience with below technologies you would be exposed but not limited to are the following:

• Expertise in Cisco UCS: B-Series/C-Series servers, Fabric Interconnects, UCS Manager
• Proficient with benchmarking tools: SPEC, FIO, Vdbench, MLPerf
• Skilled in virtualization: VMware vSphere, Microsoft Hyper-V, KVM
• Knowledge of storage systems: SAN, NAS, NVMe performance
• Experience with hardware acceleration: CPUs, GPUs for AI/ML
• Proficient in automation tools: Cisco Intersight, PowerTool
• Compute, network, and AI/ML benchmarking experience
• Flexible, enthusiastic, and quick to learn new technologies
• Excellent troubleshooting and problem-solving skills
• Strong interpersonal skills: experience creating standard methodologies guides and technical whitepapers
• Expertise in hardware optimization and performance tuning, especially for servers and AI systems

Desired Skills

• Experience in performance engineering, especially AI/ML systems
• Performance benchmarking experience (MLPerf, SPEC, FIO) is a plus
• Proven foundation in server hardware, virtualization, HCI, storage, and networking
• Deep understanding of server architecture (CPU/GPU utilization, memory management, networking)
• Knowledge of HPC, GPU workloads, and AI infrastructure components
• Ensures data integrity through purpose and governance
• Strong problem-solving skills with the ability to make complex decisions
• Ability to navigate between big-picture concepts and implementation details
• Understand high-performance computing (HPC), GPU workloads, and other AI infrastructure components.
• Optimize UCS compute infrastructure for high-performance AI/ML training and inference.
• Analyse computational efficiency, latency, throughput, and resource utilization.
• Evaluate AI platform performance using profiling and benchmarking tools.
• Hands-on experience with AI-related MLPerf benchmarks is highly desirable.

We tackle whatever challenges come our way. We have each other’s backs, we recognize our accomplishments, and we grow together. We celebrate and support one another – from big and small things in life to big career moments. And giving back is in our DNA (we get 10 days off each year to do just that).