20 hours ago
Bengaluru, IndiaSenior
Responsibilities
- Characterize and optimize LLM and Agentic AI workloads across the complete software and hardware stack.
- Identify performance bottlenecks across AI frameworks, inference runtimes, operating systems, memory, compute, and platform architecture.
- Design and develop hardware-aware and hardware-agnostic optimizations for AI frameworks and runtimes.
- Optimize LLM inference techniques including KV-cache management, attention, continuous batching, and quantization.
- Work hands-on with serving stacks such as vLLM, SGLang, and TGI.
- Analyze host and accelerator performance using VTune, EMON/PMU, perf, top-down analysis, and roofline modeling.
- Debug performance issues spanning Python frameworks, native code, Linux, runtime libraries, and hardware.
- Translate performance findings into software changes, upstream contributions, best-known configurations, and reusable optimization guidance.
- Collaborate with open-source communities and translate silicon-level findings for framework developers and application requirements for hardware architects.
Requirements
- Bachelor of Engineering with 10+ years of experience or M.Tech with 8+ years of experience in Computer Science, Computer Engineering, Electrical Engineering, or a related discipline.
- Significant hands-on experience in performance engineering, systems optimization, or workload characterization on server-class platforms.
- Demonstrated ability to identify complex performance bottlenecks and deliver measurable performance improvements.
- Strong programming skills in Python and C++, or equivalent systems programming experience in C or Rust.
- Strong understanding of cache hierarchy, memory bandwidth, NUMA, interconnects, and system-level performance behavior.
- Hands-on experience with Linux performance and system technologies such as affinity, huge pages, cgroups, eBPF, ftrace, and perf.
- Deep understanding of LLM inference, including KV-cache, paged attention, continuous batching, and quantization such as INT8, INT4, or FP8.
- Experience modifying or optimizing AI serving stacks such as vLLM, SGLang, TGI, or OpenVINO.
- Experience building, profiling, or optimizing Agentic AI systems using LangGraph, CrewAI, AutoGen, MCP-based frameworks, or similar platforms.
- Experience with hardware counter-level performance analysis and contributions to significant open-source projects, including upstream code contributions.
- Ability to communicate across abstraction layers with software developers and hardware architects.
Benefits
- Hybrid work model allowing employees to split time between the assigned Intel site and off-site.
- Experienced-hire role based in Bangalore, India, on Shift 1.
- Intel states that it does not charge recruitment, medical examination, or other hiring fees.
Categories
About Intel
Intel is a public semiconductor company that designs and manufactures CPUs and other silicon for PCs, servers, networking, edge, and embedded systems, and also offers foundry services plus AI and graphics accelerators. Founded in 1968 and headquartered in Santa Clara, it sells primarily to OEMs, cloud providers, and device makers worldwide. Its portfolio includes x86 processors (Core and Xeon), Ethernet and chipset products, and the Mobileye autonomous driving platform.