Company:Qualcomm India Private Limited

Job Area:Engineering Group, Engineering Group > Systems Engineering

General Summary:

Job Overview

You will be part of Automotive Product Performance team that is responsible for debug, characterization and performance optimization of applications and middleware in various OSs by tuning various settings in software and system. Great opportunity to work on multiple OSs like QNX, Android, Linux and other real time operating systems, virtualization solutions like Hypervisor, Multi-visor, RedHat Linux, and Linux Containers.

Responsibilities include:

Working closely with cross functional & other performance team across regions to drive various performance activities.

Optimize scheduler performance & loading migration between CPU cores especially in a big-little CPU architecture.

Evaluate performance of various IP cores like CPU, GPU, DDR and AI accelerators with benchmarks like Antutu, LM Bench, GeekBench, GfxBench or ADASMark.

Evaluate new benchmarks, cross-compile on different OS’es and performance optimize for QCOM chipsets.

Perform competitive analysis study of different benchmarks.

Evaluate and develop various cross platform performance tools & applications for concurrency usecases.

Perform CPU, GPU & Memory, System Cache analysis, validate the accuracy of tools and optimize software performance in each OS to meet target scores.

Follow closely on the latest compiler options to optimize performance for ARM chipsets and evaluate performance power tradeoffs.

Evaluate performance of Hypervisor operating systems with benchmarks and real-world multi display and multi camera concurrency applications on multiple Guest VMs and identify the overhead and interrupt latency times.

Evaluate and characterize performance at various junction temperatures and optimize to run at high ambient temperatures.

Understand necessary OS internals and SW architecture that helps optimize the performance of overall system.

Minimum Qualifications

5+ years of industry experience in the following:

Strong experience in optimizing SW performance in any Linux based operating system.

Exposure to working in QNX and Android Operating system and its software architecture.

Prior experience in performance optimizations of real time RedHat safe Linux in a virtualized environment and working with upstream community.

Experience working with various cross compilers like arm gcc and ability to understand compile optimizations.

Prior experience in compiling large code base & exposure to software development life cycle.

Must have used any benchmarks or workloads to characterize performance or to meet KPIs.

Must have the ability to analyze the performance measurements provided by the test teams and guide them with required new test cases.

Preferred Qualifications

Additional skills in the following areas are preferred:

Collaborate with multiple teams and create professional quality reports and slides using MSOffice or any advanced visualization tools.

Knowledge on any multimedia frameworks like OpenGL/ES, OpenMax and OpenCL is plus.

Optionally, develop UI applications preferably using cross platform frameworks like Qt.

Knowledge on Android Software architecture or Westin, GWES is a plus.

Exposure to any Automotive operating systems like AGL, QNX, Hypervisor or GreenHills.

Candidates with Machine learning\Deep learning and exposure to AI accelerators.

Education Requirements

Required: Candidate with bachelor’s and 5+ years of experience.

Preferred: Candidate with Masters and 3+ years of experience.

Keywords

Software Performance, Linux, RedHat, Scheduler, Automotive Performance, Android, Operating System, Benchmarks, Boot Optimization, QNX, Green Hills, Hypervisor, Development

Minimum Qualifications:

•    Bachelor's degree in Engineering, Information Systems, Computer Science, or related field and 4+ years of Systems Engineering or related work experience.
OR
Master's degree in Engineering, Information Systems, Computer Science, or related field and 3+ years of Systems Engineering or related work experience.
OR
PhD in Engineering, Information Systems, Computer Science, or related field and 2+ years of Systems Engineering or related work experience.

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