NXP Semiconductors
Software Engineer- Modelzoo
Employment
Full-timeFrom the employer
Full time
Level
Not statedCategory
EngineeringCountry assessment
Not doable from Austria because it is tied to an office and never says it can be done remotely.
Our assessment is guidance. Confirm arrangements with the employer.
Skills mentioned in this posting
Job description
Software Engineer - Modelzoo
Company:** Kinara Inc. USA
---
Job Summary
We are seeking a talented and innovative Software Engineer to join our Modelzoo team. In this role, you will be instrumental in the development, optimization, and deployment of machine learning models for Kinara's cutting-edge AI inference solutions. Your work will directly impact the performance and capabilities of our hardware and software products.
---
Job Responsibilities
* Design, implement, and optimize machine learning models for various applications, focusing on efficiency and performance on Kinara's AI processors.
* Develop and maintain the Modelzoo framework, including tools for model conversion, quantization, and deployment.
* Collaborate with hardware and software teams to ensure seamless integration of models and achieve optimal end-to-end system performance.
* Conduct performance profiling and analysis of models, identifying bottlenecks and implementing solutions for improvement.
* Research and evaluate new machine learning algorithms and techniques to enhance model accuracy and efficiency.
* Create and maintain comprehensive documentation for models, tools, and processes within the Modelzoo.
* Participate in code reviews and contribute to the overall quality and maintainability of the codebase.
* Stay up-to-date with the latest advancements in machine learning, deep learning, and AI hardware.
---
Job Qualifications
* Bachelor's or Master's degree in Computer Science, Electrical Engineering, or a related field.
* 2+ years of experience in software development, with a strong focus on machine learning or deep learning.
* Proficiency in Python and experience with machine learning frameworks such as TensorFlow, PyTorch, or JAX.
* Solid understanding of machine learning concepts, including model architectures (e.g., CNNs, Transformers), training methodologies, and evaluation metrics.
* Experience with model optimization techniques such as quantization, pruning, and knowledge distillation.
* Familiarity with embedded systems or AI accelerator architectures is a plus.
* Strong problem-solving skills and the ability to debug complex issues.
* Excellent communication and collaboration skills, with the ability to work effectively in a team environment.
* Experience with version control systems (e.g., Git).