What You'll Be Doing
- You will be part of NVIDIA re-targetable GPU compiler backend team
- You will contribute to compiler optimizations to produce best-in-class, robust, supportable compiler and tools
- Work on challenging problems in register allocation, instruction scheduling, synchronization, loop optimizations etc.
- Develop innovative solutions to optimize workloads in Deep Learning, Ray Tracing, HPC etc. by working with industry experts in each field.
- Solve unique problems seen only in compiling for massively parallel GPU architecture.
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Get a chance to influence and work on new GPU architectures.
- B.S. or higher degree in Computer Science/Engineering
- Proficient in compiler design with 5+ years of experience
- Strong background in program analysis and high level optimizations
- Excellent C and C++ programming skills
- Hands on experience in compiler infrastructures like LLVM/GCC
- Good understanding of processor architecture
- Experience in working in a global team
- Self-motivated to get things done
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Good communication skills with ability to influence others
- Masters or PhD preferred, with 8+ years of relevant experience
- Demonstrated ability to pursue complex optimization problems
- Experience in Scheduling/Register Allocation
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Experience in developing CUDA, DirectX, OpenGL/Vulkan applications
NVIDIA is committed to developing a diverse work environment and is proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.
JR1999085
Senior Embedded Software Engineer
@ Embedd 
What we're looking for
At embedd.it, we power hardware-software integration in embedded devices. We turn fragmented semiconductor chip data into configurable digital twins, then deterministically generate code, tests, and documentation – making integration faster, cheaper, and resilient to supply chain shocks.
We’re looking for a true legend – someone with abstract thinking and deep expertise in low-level software development. You’ll build vendor-agnostic tooling for MCU and peripheral integration to solve hardware-software integration once and for all. We work at the intersection of embedded systems, code generation, compilers, and machine learning. It’s your chance to help redefine how low-level development is done.
Responsibilities
- Drive the architecture of the driver structures and system layout
- Define scalable patterns for cross-architectural integration across bare-metal, Zephyr, Linux, and other environments
- Deconstruct complex SoC device trees and translate hardware descriptions into structured internal models for automated reasoning
- Partner with the ML team to shape data and annotation models for AI-driven data-extraction tooling
Qualifications
- 5+ years of experience in embedded systems development, including bare-metal and RTOS-based systems
- Proficiency in C/C++
- Familiarity with firmware configuration, SoC bring-up, and system-level debugging
- Hands-on experience with code generation tools, or low-level compiler/decompiler/emulator technologies
- Strong background in embedded toolchains: compilers, linkers, debuggers, and build systems
- Python or scripting for automation and tooling is a plus
- Experience with functional-safety standards is a plus
Why embedd.it?
- Dynamic, venture-backed team of engineers challenging the status quo 🚀
- Work at the intersection of embedded systems, code generators, compilers, and ML 🤖
- Unusual challenges requiring out-of-the-box abstract thinking 🧠
- Competitive compensation: cash + equity 💰
- Remote work possible 🌍
About Us
embedd.it is a UK-based startup reinventing embedded development. Our platform transforms unstructured semiconductor data into structured digital twins, enabling automatic generation of drivers, tests, and documentation. We're building a single, traceable source of truth to make integration fast, vendor-agnostic, and future-proof.
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