Jobs
Benefits & Perks
•Learning Budget
•Collaborative work environment
•Learning
Required Skills
Python
C/C++
Machine Learning
Deep Learning
Computer Vision
Hugging Face
Linux
CI/CD
Git
Senior AI Software Engineer
Company: NXP Semiconductors México, S. de R.L. de C.V.
About the Role
NXP offers an inclusive, collaborative, and innovation-driven work culture where engineers have the freedom to explore ideas, contribute to cutting-edge technologies, and grow their technical depth.
As part of ongoing enhancements to our Discrete NPU Model Zoo, we are looking for AI Engineers to contribute to the design, development, and optimization of model‑zoo infrastructure supporting next‑generation computer vision, generative AI, and LLM workloads. You will work on developing compilation, inference, and performance workflows for AI accelerators, while helping build end‑to‑end demos and benchmarking pipelines.
CNN Model Zoo Responsibilities
- Collaborate on scaling up our CNN‑based model zoo
- Add new models and their variants in both Python and C++
- Improve accuracy across ~50 existing models
- Re‑implement variant models in Py Torch for integration with the MCW tool
- Use the MCW tool for optimization, pruning, and performance tuning
- Automate model testing, validation, and optimization flows where feasible
- Develop gstreamer / NXP nnstreamer plugins and end‑to‑end inference pipelines
- Build high‑quality demos showcasing model capabilities on NPU accelerators
LLM/VLM Model Zoo Responsibilities
- Contribute to the development and expansion of the LLM model zoo
- Use Hugging Face APIs to build required pipelines and workflows (Python and C++)
- Integrate and support multiple variants of LLMs and VLMs
- Develop automated testing frameworks and Jenkins‑based CI pipelines
- Execute benchmarking, performance profiling, and validation of LLM/VLM models
- Build demos demonstrating large‑model capabilities on our NPU platforms
Qualifications
- Bachelor's degree in Electronics/Computer/Systems/Robotics Engineering or similar with 5+ years of experience in Machine Learning or related fields
- Strong proficiency in Python (AI scripting & workload automation) and C/C++ (low‑level performance work)
- Solid understanding of deep learning architectures across CV, NLP, or generative models
- Experience building demos/applications using CNN and LLM models
- Ability to measure and report latency, throughput, accuracy, and power for AI workloads
- Familiarity with LLM benchmarking frameworks such as MMLU, Human Eval, GSM8K, ARC Challenge, GPQA, etc.
- Experience working with Hugging Face APIs, model repositories, and deployment workflows
- Knowledge of Linux environments, build systems, and optionally, driver‑level basics
- Experience with GitHub, CI/CD pipelines, and automated testing frameworks
- Fluency in English (written and spoken) is required
Preferred Qualifications
- Experience with NPU architectures, compiler toolchains, and runtime environments
- Exposure to a variety of AI/ML/DL frameworks such as Tensor Flow, Py Torch, Caffe, and ONNX pipelines
- Strong skills in developing AI workflows in both C++ and Python
- Experience in hardware/software performance evaluation and profiling
- Ability to work effectively both independently and in collaborative team settings
- Strong aptitude for learning new tools, technologies, and AI workflows quickly
What You Will Gain
- Hands‑on experience with AI accelerator hardware, NXP SDKs, and next‑generation AI solutions
- Opportunity to work with a wide range of customer models across CV, LLM, VLM, and Generative AI domains
- Deep exposure to end‑to‑end AI pipelines, benchmarking methodologies, and model‑zoo development
- Learning environment focused on innovation, performance optimization, and practical deployment of AI workloads
About NXP Semiconductors
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 Notes
- Are you already an NXP employee? Do not apply here. Instead, you must apply via our internal career page.
- 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.
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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%
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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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