채용
Intern (f/m/d) for Edge AI Model Zoo Optimization Research & Engineering
Munich
·
On-site
·
Internship
·
5d ago
Required Skills
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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About NXP Semiconductors
Reviews
3.9
44 reviews
Work Life Balance
3.8
Compensation
3.9
Culture
4.1
Career
3.6
Management
3.8
73%
Recommend to a Friend
Pros
Competitive compensation and benefits
Good work-life balance and flexible environment
Interesting projects and challenges
Cons
Room for improvement in processes
Work-life balance varies by team
Internal communication could improve
Salary Ranges
267 data points
Junior/L3
L3
Junior/L3 · Data Scientist
0 reports
$114,000
total / year
Base
$99,000
Stock
-
Bonus
$15,000
$96,900
$131,100
Interview Experience
42 interviews
Difficulty
3.1
/ 5
Duration
14-28 weeks
Offer Rate
33%
Experience
Positive 69%
Neutral 13%
Negative 18%
Interview Process
1
Phone Screen
2
Technical Interview
3
Hiring Manager
4
Team Fit
Common Questions
Technical skills
Past experience
Team collaboration
Problem solving
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