Job Title: Software Engineer (2-3 years experience)
Job Summary
We're looking for a skilled and motivated Machine Learning Software to join our team. The ideal candidate will have a solid foundation in deep learning and a strong interest in optimizing and deploying ML models on specialized hardware. This role involves implementing model optimizations, with a particular focus on quantization, to improve the performance of machine learning inference on target platforms.
Key Responsibilities
- Model Porting & Deployment: Port and deploy deep learning models from frameworks like PyTorch and TensorFlow to proprietary or commercial ML accelerator hardware platforms.
- Performance Optimization: Analyze and improve the performance of ML models for target hardware, focusing on latency and throughput.
- Quantization: Contribute to model quantization efforts (e.g., INT8) to reduce model size and accelerate inference while maintaining model accuracy.
- Profiling & Debugging: Use profiling tools to identify and fix performance bottlenecks in the ML inference pipeline on the accelerator.
Required Qualifications
Technical Skills:
- Proficiency in deep learning frameworks such as PyTorch and TensorFlow.
- Hands-on experience with deploying and optimizing models on GPUs or other specialized accelerators.
- Some experience with model quantization (Post-Training Quantization).
- Strong proficiency in C++ and Python.
- Experience with GPU programming models like CUDA/cuDNN is a plus.
- Familiarity with ML inference engines and runtimes (e.g., TensorRT, OpenVINO, TensorFlow Lite).
- Foundational understanding of computer architecture principles.
- Version Control: Proficient with Git and collaborative development workflows.
- Education: Bachelor's or Master's degree in Computer Science, Electrical Engineering, or a related field.
Preferred Qualifications
- Knowledge of hardware-aware model design.
- Familiarity with compiler technologies for deep learning.
- Experience with real-time or embedded systems.
- Knowledge of cloud platforms (AWS, GCP, Azure).
- Experience with CI/CD pipelines for ML models.
More information about NXP in India...
#LI-2734Skills Required
- Proficiency in PyTorch and TensorFlow
- Hands-on experience deploying and optimizing models on GPUs or other specialized accelerators
- Experience with model quantization (Post-Training Quantization, INT8)
- Strong proficiency in C++
- Strong proficiency in Python
- Experience with GPU programming models (CUDA/cuDNN)
- Familiarity with ML inference engines and runtimes (TensorRT, OpenVINO, TensorFlow Lite)
- Foundational understanding of computer architecture principles
- Proficient with Git and collaborative development workflows
- Bachelor's or Master's degree in Computer Science, Electrical Engineering, or related field
- Knowledge of hardware-aware model design
- Familiarity with compiler technologies for deep learning
- Experience with real-time or embedded systems
- Knowledge of cloud platforms (AWS, GCP, Azure)
- Experience with CI/CD pipelines for ML models
NXP Semiconductors Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about NXP Semiconductors and has not been reviewed or approved by NXP Semiconductors.
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Retirement Support — Feedback suggests the 401(k) program is strong, with reports of a 100% match on the first 5% of base salary. This is seen as a solid pillar of the overall rewards package.
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Equity Value & Accessibility — An employee stock purchase plan with a 15% discount is highlighted as a meaningful benefit. This feature adds perceived long-term value beyond base pay.
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Healthcare Strength — Medical, dental, and vision coverage alongside HSA/FSA options and wellness incentives are described as comprehensive. These offerings contribute to a sense of robust core benefits.
NXP Semiconductors Insights
What We Do
NXP Semiconductors N.V. (NASDAQ: NXPI) enables a smarter, safer and more sustainable world through innovation. As a world leader in secure connectivity solutions for embedded applications, NXP is pushing boundaries in the automotive, industrial & IoT, mobile, and communication infrastructure markets. Built on more than 60 years of combined experience and expertise, the company has approximately 34,500 employees in more than 30 countries and posted revenue of $13.21 billion in 2022. Find out more at www.nxp.com. Privacy Policy: https://www.nxp.com/company/about-nxp/privacy-policy-for-social-media-pages:PRIVACY-POLICY-SOCIAL-MEDIA
