Imaging and Multimedia Systems Software Engineer
2 weeks ago
Minimum qualifications:
Bachelor's degree or equivalent practical experience.
5 years of experience in software development using C/C++, alongside a strong foundation in data structures and algorithms. 3 years of experience with embedded operating systems tailored for mobile System-on-Chip (SoC) platforms, and at least 1 year in software design and architecture. 3 years of experience in system software development, encompassing both kernel and user mode drivers, Hardware Abstraction Layer (HAL), and multimedia subsystems (Camera ISP, Video, GPU, and Display).
Preferred qualifications:
Proficiency in system architecture analysis for intricate imaging and multimedia user experiences to pinpoint performance and power limitations.
Experience in collaborating with teams and stakeholders to launch features and use-cases on mobile devices.
Familiarity with software development in Python or Java.
Experience in developing and optimizing machine learning inference pipelines.
Knowledge of graphics processing unit and digital signal processing software development for imaging, computer vision, and multimedia applications utilizing programming languages (e.g., OpenCL, Vulkan, CUDA, Halide, and architecture-specific C/C++ intrinsics). Understanding of mobile SoC architecture and multimedia subsystems (Camera ISP, TPU/NPU, GPU, Video Codecs, Display Engine, and Security).
About the role:
Google's software engineers are at the forefront of developing next-generation technologies that transform how billions of users connect, explore, and interact with information and each other.
We seek engineers who contribute innovative ideas from diverse fields, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design, and mobile technology; the list is ever-expanding.
As a software engineer, you will engage in projects vital to Google's objectives, with opportunities to transition between teams and projects as our dynamic business evolves.
We expect our engineers to be adaptable, exhibit leadership qualities, and be eager to tackle new challenges across the full technology stack as we continue to advance technology.
In this capacity, you will develop Google Tensor, a System-on-Chip (SoC) that powers the latest Pixel devices.
You will bring the latest Machine Learning (ML) innovations and research to fruition by delivering integrated computing hardware and software.Google's mission is to organize the world's information and make it universally accessible and useful. Our team merges the best of Google AI, Software, and Hardware to create radically helpful experiences. We research, design, and develop new technologies and hardware to enhance computing speed, seamlessness, and power. Our goal is to improve people's lives through technology.
Compensation:
The US base salary range for this full-time position is $161,000-$239,000 + bonus + equity + benefits. Salary ranges are determined by role, level, and location.
The displayed range reflects the minimum and maximum target salaries for the position across all US locations.
Individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training.
More specific salary range details can be provided during the hiring process.
Responsibilities:
Contribute to the architecture and design of imaging and multimedia systems for Google's Tensor SoCs and Pixel devices.
Develop prototype and production software across the Android camera and multimedia stack, including kernel and user mode drivers, HAL, and framework, as well as the Machine Learning (ML) stack and applications to validate the feasibility of new and emerging use-cases on future Tensor SoCs.
Collaborate with multimedia IP and architecture, system architecture, and device software teams to transition prototypes into production.Conduct thorough system analysis for complex imaging and multimedia user experiences to identify performance and power bottlenecks, and communicate the analysis results in both quantitative and qualitative terms.
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