Leading company in the semiconductor industry
Intern (f/m/d) for Edge AI Model Zoo Optimization Research & Engineering
必須スキル
Python
Git
Linux
PyTorch
TensorFlow
Machine Learning
Are you fascinated by the evolving landscape of Edge AI and Efficient Generative Architectures running on Edge AI devices and are eager to explore the potential of this technology in real-world scenarios? Do you want to contribute to cutting-edge research and development in optimizing AI workloads while gaining hands-on experience in a high-tech environment? Then join the AI IP and Solutions team at NXP and help shape the future of intelligent systems.
Key responsibilities:
At the AI IP and Solutions team, we are looking for a candidate passionate about Edge AI model optimization methods and their application to edge‑born use cases. You will be part of a team conducting research, innovation, and engineering in the Edge AI domain.
Your work will involve exploring and researching state‑of‑the‑art model compression methods for CNNs and Language Models across different frameworks, and benchmarking their performance, modularity, and integration potential with NXP’s embedded systems.
Your tasks will include but not limited to:
- Integrate a growing set of Discriminative and Generative Models into our internal Model Zoo.
- Automate model benchmarking across accuracy, latency, memory footprint, and hardware utilization.
- Explore and evaluate model optimization techniques on NXP ’s embedded systems.
- Document findings and contribute to internal knowledge bases and tooling.
- Collaborate with team members to identify promising directions for future development.
Preferred skills:
- Solid understanding of AI/ML fundamentals, especially CNNs and Generative models (eg., LLMs/VLMs) and experience with libraries such as Py Torch and/or Tensor Flow.
- Strong hands-on experience with Python and software development best practices (e.g., modular design, testing).
- Familiarity with model compression techniques, such as Quantization, Pruning, or Knowledge Distillation.
- Basic knowledge of Linux & Git.
- Familiarity with RESTful API development and frameworks such as FastAPI, including experience interacting with OpenAI‑compatible inference endpoints.
- Experience with edge AI deployment (e.g., TFLite, ONNX, Executorch) is a plus.
Your profile:
- Currently pursuing a master’s degree in computer science, Artificial Intelligence, Machine Learning, or a related field.
- Strong analytical and problem-solving skills with the ability to work independently.
- Excellent English communication skills for collaboration with our multinational team across multiple sites.
- Enthusiastic about exploring new technologies and contributing to impactful AI research.
What NXP Offers:
- A monthly salary of €2,420.00
- Flexible working hours
- The possibility to work in a hybrid setup
- 2.5 days of vacation per month incase of volutary internship
- Access to an on-site cafeteria
- Networking initiatives and Employee Resource Groups such as Young Community, No Extra Planet, NXP Equal, Women in NXP, and more — fostering both professional and personal exchange
Please note:
The successful candidate may/will be responsible for security related tasks.
The assignment may/will be in scope of security certifications, therefore a conscious and reliable way of working is necessary.
More information about NXP in Germany...
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NXP Semiconductorsについて
NXP Semiconductors
PublicNXP Semiconductors produces secure connectivity solutions for embedded applications.
10,001+
従業員数
Eindhoven
本社所在地
$45B
企業価値
レビュー
10件のレビュー
3.7
10件のレビュー
ワークライフバランス
3.5
報酬
4.0
企業文化
3.8
キャリア
3.2
経営陣
3.0
72%
知人への推奨率
良い点
Supportive management and colleagues
Innovation and interesting technology
Good work-life balance and flexible hours
改善点
Management issues and poor communication
Limited career advancement and training
Heavy workload and long hours
給与レンジ
227件のデータ
Junior/L3
Intern
L3
Junior/L3 · Data Scientist
0件のレポート
$114,000
年収総額
基本給
$99,000
ストック
-
ボーナス
$15,000
$96,900
$131,100
面接レビュー
レビュー42件
難易度
3.1
/ 5
期間
14-28週間
内定率
33%
体験
ポジティブ 69%
普通 13%
ネガティブ 18%
面接プロセス
1
Phone Screen
2
Technical Interview
3
Hiring Manager
4
Team Fit
よくある質問
Technical skills
Past experience
Team collaboration
Problem solving
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