Automotive Product Performance Engineer

Job Title R&D – Automotive Product Performance Engineer
Job Area Engineering - Software
Location China – Shanghai
General Summary:
You will be responsible for optimizing performance & root-causing performance-related issues when use-cases are running on Snapdragon Automotive chipsets.
Responsibilities include:
• Profile, analyze the traces and optimize the performance of complex concurrent applications running on OSes such as QNX, Linux and Android running Natively as well as in virtual environments on Qualcomm Automotive platforms.
• Enable new use-cases & benchmarks on Auto platforms working with multiple HW & SW teams.
• Use Performance tools to analyze the load patterns across IPs and identify performance bottlenecks in system.
• Analyze Performance KPIs of Automotive use-cases such as Booting, Multimedia (Camera, Display, Video playback), ADAS (Front and Surround camera perception, Driver Monitoring, Parking stack), Maps & Navigation, Rear-seat entertainment etc. Correlate performance with projections from the systems team.
• Use deep systems understanding to fine-tune HW & SW knobs (voltages, frequencies, boot options & features, QoS and NoC configurations, stack parameters) to optimize for performance.
• Maintain & publish a performance dashboard across all critical use-cases.
• Work with CE teams and customers to root-cause performance issues and lead deep-dive debugs of customer use-cases in HW.
• Collaborate with cross-functional global teams to plan, execute performance activities on Auto chipsets as well make recommendations for next generation chipsets.
• Evaluate and characterize performance at various junction temperatures and optimize to run at high ambient temperatures.
• Evaluate impact on System Power due to power / thermal features and make recommendations to optimize thermal behavior.
• Enable Proof-of-Concepts working with partner teams, CE and customers.
• Work with CA team to conduct performance comparison with competitive solutions.
Minimum Qualifications:
• Bachelor's degree in Engineering, Information Systems, Computer Science, or related field and 8+ years of Systems Engineering or related work experience.
OR
Master's degree in Engineering, Information Systems, Computer Science, or related field and 7+ years of Systems Engineering or related work experience.
OR
PhD in Engineering, Information Systems, Computer Science, or related field and 6+ years of Systems Engineering or related work experience.
Preferred Qualifications:
10+ years of industry experience in the following:
• Strong debugging\SW development experience in debugging systems and software issues preferably on Automotive\Mobile\IoT chipsets.
• Knowledge of Hypervisors.
• Understanding of compiler optimizations.
• Quick learner and able to adapt to new technologies such as ADAS, Functional safety, Different OSes.
• Must have excellent communication and presentation skills.
• Working knowledge of Machine Learning and hardware accelerators.
• Have strong working knowledge on various IP cores like CPU, GPU, DDR, DSP and have ability to assess the performance with benchmarks like Dhrystone, Antutu, GeekBench, GfxBench, SpectInt etc.
Additional skills in the following areas are preferred:
• Basic Knowledge on any multimedia frameworks like OpenGL/ES, OpenMax and OpenCL is plus.
• Knowledge on Computer architecture or Bus/NOC profiling is big plus.
• Strong knowledge of ML and NSP is a big plus
• Exposure to Automotive operating systems like AGL/QNX/Hypervisor & experience working on any Automotive applications.
• Experience in PoC development and competitive analysis Knowledge on Voltage/Power/Thermal domain is plus.
Keywords
Architecture Performance, System Performance, Automotive Performance, Benchmarks, Thermal Performance, UX optimization, QNX, Hypervisor, Application Development, ADAS, Automotive
Level of Responsibility:
• Requires verbal and written communication skills to convey highly complex and/or detailed information.
• Tasks often require multiple steps which can be performed in various orders; extensive planning, problem-solving, and prioritization must occur to complete the tasks effectively.