Senior SDE- Kernel Engineer, SSG

Amazon is hiring a Senior SDE- Kernel Engineer, SSG in Bengaluru, India. Level rates it ; you can apply on Amazon.

Level's read on this job

Little AI ●○○○ is how Level rates this software engineer role: aI is not part of the work.
The posting mentions computer vision among its tools and skills.
Level classes it as a senior role.
Amazon has 20,000+ other open roles on Level.

AI in this role

computer-vision

The Amazon Devices team designs and engineers high-profile consumer electronics, including the best-selling Kindle family of products. We have also produced groundbreaking devices like Fire tablets, Fire TV, Amazon Dash, and Amazon Echo. What will you help us create?

As a Sr Kernel Engineer you will help build the kernel stack and BSP for various SoCs with custom hardware accelerators to be deployed in a range of Amazon devices. You will develop software for industry standard and custom hardware IP to accelerate applications in machine learning, computer vision and robotics.

In this role you will:
- Develop and modify Board Support Package (BSP) components: This includes bootloaders (TF-A, OP-TEE, SCP, U-Boot), device drivers, kernel modules, and device tree support.
- Collaborate with architecture teams to define and implement innovative silicon features.
- Perform initial silicon and platform bring-up in both pre-silicon and post-silicon environments.
- Debug and root-cause complex issues across hardware and software interfaces.
- Partner with cross-functional teams to productize silicon solutions and ensure successful product delivery.
- Optimize OS and kernel solutions to achieve excellent performance for supported features.
- Contribute throughout product development stages including HVT, EVT, DVT, and PVT phases.
- Engage with diverse cross-functional teams to ensure seamless feature integration and alignment across hardware, firmware, and software components.

Basic qualifications

- 10+ years of non-internship professional software development experience
- 10+ years of programming with at least one software programming language experience
- 10+ years of leading design or architecture (design patterns, reliability and scaling) of new and existing systems experience
- Experience as a mentor, tech lead or leading an engineering team
- Hands-on experience with ARM v8/v9 architecture profiles, including understanding of instruction sets, memory models, and security features.
- Demonstrated ability to debug complex system-level issues on embedded devices, including hardware-software integration challenges.

Preferred qualifications

- 10+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience
- Bachelor's degree in computer science or equivalent
- Hands-on experience with embedded Linux Yocto distribution for custom BSP development.
- Strong knowledge of thermal management, power optimization, and performance tuning.
- Proven experience with high-speed interfaces including USB, eMMC, NAND, and PCIe.
- Proficiency with low-speed interfaces such as Pinmux, GPIO, SPI, I2C, UART, and PWM.
- Solid understanding of ARM security architecture, including ARM TrustZone technology.

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.

How we rate this

Senior SDE- Kernel Engineer, SSG at Amazon rates 35 out of 100 for how much of the daily work is AI. That makes it Little AI (AI Level 1 of 4). The level is about AI in the job, not seniority.

Classification

Little AI. AI is not part of the work.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.