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# Software Engineer (Architecture)

- **Company:** Targeted Talent
- **Location:** Las Vegas, NV, United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Artificial Neural Networks, C++ (Programming Language), Compilers, Python (Programming Language), Machine Learning, Software Tools, Software Engineering, Graphics Processing Unit (GPU), Deep Learning, Parallel Computation, Information Technology, Hardware Acceleration
- **Published:** September 26, 2026
- **Apply:** https://www.juju.com/job/16_d384014741

## About the Role

* 10+ years of experience developing software for a variety of highly parallel architectures.
 * Previous roles include experience with optimizing algorithms for hardware acceleration machine learning accelerators, spatial architectures, or GPUs.
 * Strong problem-solving skills and the ability to resolve complex issues with a high level of ambiguity.
 * Understanding of Deep Learning fundamentals.
 * Strong development skills in C/C++, Python.
 * Superb soft skills: ability to work efficiently and effectively in a group environment, and influence a cross-functional team without having direct managerial authority.
 * Computer Science, Engineering, or related degree; preferably MS or PhD.
 * Driven and self-directed.

## Description

* Advance the state of the art in compiler and runtime technology for delivering high-performance acceleration of AI workloads across a variety of neural network architectures.
 * Research and design new software and hardware AI solutions, involving simulators, optimizing compilers, code generators, and runtime execution frameworks for deep learning accelerators.
 * Evaluate various trade-offs of different parallelization strategies such as performance, power, energy, and memory consumption.
 * Enhance AI software tools to support the latest and greatest DNNs emerging from the research community and industry.
 * Keep up with the fast-paced development happening in the industry and academia to continuously enhance our products.
 * Work closely with other software and hardware engineers to develop the next generation of deep learning software.
 * Collaborate with architects and hardware engineers to co-design future accelerators.


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