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Internship / Thesis Student for Edge AI Optimization & LLM Quantization (f/m/d)
Internship / Thesis Student for Edge AI Optimization & LLM Quantization (f/m/d)
3 Locations
·
On-site
·
Internship
·
2w ago
Benefits & Perks
•Learning Budget
•Learning
Required Skills
Problem-solving
English communication
The future starts here! Ready to join NXP?
Are you inspired by the rapidly evolving world of Edge AI and Efficient Generative Architectures on edge devices, and excited about exploring how these technologies can make a meaningful impact in real‑world applications? Do you want to contribute to cutting-edge research and development that optimizes AI workloads while gaining hands‑on experience in a supportive, high‑tech environment? Join the Artificial Intelligence Competence Center at NXP and play a key part in shaping the future of intelligent systems.
Your Team
At the AI Competence Center, we welcome motivated students who are enthusiastic about Edge AI model and system optimization methods and their applications in emerging edge‑born use cases, such as Edge Agentic AI. You will join a collaborative team focused on research, innovation, and engineering in Edge AI. You will have the opportunity to explore and develop state‑of‑the‑art model compression methods and inference‑time optimizations for Small Language Models and Vision Language Models. Together with the team, you will evaluate the performance of optimized models and systems on NXP's embedded systems and will help potential integration of developed methods in NXP's embedded systems.
Your Responsibilities
- Exploring, designing, and implementing model compression techniques (quantization, sparsity, knowledge distillation, etc.), inference optimizations (e.g., speculative decoding), and efficient generative architecture design
- Documenting findings with clarity and supporting internal knowledge sharing
- Working closely with team members to identify promising directions for future development
- Communicating research outcomes through scientific publications and/or invention disclosures
Your Profile
- Currently pursuing a Master's degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field
- Great analytical and problem‑solving skills, with the ability to work both independently and collaboratively
- Excellent English communication skills for interacting with a diverse, multinational team across multiple sites
- Curious, open‑minded, and eager to explore new technologies while contributing to meaningful and impactful AI research
Preferred Skills
- Very good understanding of AI/ML concepts (including LLMs, VLMs, Agentic AI) and experience with frameworks such as Py Torch and Tensor Flow
- Familiarity with model compression techniques such as quantization, pruning, and knowledge distillation
- Understanding of LLM inference optimization techniques including speculative decoding
- Experience with Python and modern software development practices (modular design, testing)
- Basic knowledge of Linux and Git
- Experience with edge AI deployment (e.g., TFLite, ONNX, Execu Torch) is a plus
Duration
This is a full-time internship (36/40 hours per week) with a duration of minimum six months or longer. Please note that to be considered for an internship/working student assignment at NXP, you need to be registered as a student during the entire period of the assignment. We encourage applicants to upload their grade transcripts as part of their application. While optional, it helps us gain a clearer understanding of your academic background when reviewing your profile.
About NXP
NXP Semiconductors N.V. (NASDAQ: NXPI) enables a smarter, safer, and more sustainable world through innovation. As the world leader in secure connectivity solutions for embedded applications, NXP is pushing boundaries in the automotive, industrial & IoT, mobile, and communication infrastructure markets. For more information, visit www.nxp.com
Bright Minds. Bright Futures.
We believe that a key component to growing our business is to develop our people. To enable you to grow your career at NXP, we offer online and offline learning opportunities to help you develop some of your core and professional skills.
Commitment at NXP
We recognize NXP is a powerful change agent as we continue to deliver innovative solutions that advance a more sustainable future. We remain steadfast in our commitment to sustainability and making measurable year-on-year progress. Also, we aim to create an inclusive work environment and we will not tolerate racism, discrimination or harassment of any kind. We have programs in place focused on diversity, inclusion and equality.
Important Information
Thank you for considering a career at NXP. To help you prepare for the different steps in our hiring process, see the following useful advice and tips. Are you already an NXP employee? Do not apply here. Instead, you must apply via our internal career page. Thank you for your interest in supporting our recruitment efforts. Please note that NXP operates under a strict Preferred Supplier List (PSL) for all recruitment activities. Any candidate profiles or resume submitted without a prior written agreement or explicit request from our Talent Acquisition team will be considered unsolicited. Such submissions will be deemed free of any obligations, and no fees will be paid by NXP or any of its affiliates, subsidiaries, or divisions - regardless of whether the candidate is hired, either coincidentally or otherwise. Thank you for your understanding.
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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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