AI Engineer

KEY RESPONSIBILITIES: Understand the factories, manufacturing processes, data availability and avenues for improvement Brainstorm, together with engineering, manufacturing and quality problems that can be solved using the acquired data in the data lake platform. Design, develop, deploy, and maintain AI, Machine Learning (ML), and Generative AI solutions that address business and manufacturing challenges. Build, train, fine-tune, evaluate, and optimize AI/ML models for performance, scalability, reliability, and accuracy. Develop and implement Agentic AI solutions, AI assistants, and intelligent automation systems to improve operational efficiency and decision-making. Understand from the process engineers the pain points in the process and device solutions to help and improve the process Find possible areas where faster data analysis and decision making can help the factory Analyze large, complex data sets that meet functional / non-functional business requirements. Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery for greater scalability Deploy and monitor the solution Work with data and analytics experts to strive for greater functionality in our data systems. Work together with Data Architects and data modeling teams across Nexperia BE sites. Identify the data needs and extraction process which can help improve the business KPI’s and SKILLS /COMPETENCIES (Top 3-7 most important/critical competencies needed for the job both soft and hard skills): Good knowledge of the business vertical with prior experience in solving different use cases in the manufacturing or similar industry Ability to bring cross industry learning to benefit the use cases aimed at improving manufacturing process at Nexperia Problem Scoping/definition Skills: Experience in problem scoping, solving, quantification Strong analytic skills related to working with unstructured datasets. Build processes supporting data transformation, data structures, metadata, dependency, and workload management. Working knowledge of message queuing, stream processing, and highly scalable ‘big data’ data stores Ability to foresee and identify all right data required to solve the problem AI Skills: Machine Learning model development and deployment Deep Learning (TensorFlow, PyTorch, Keras) Predictive Analytics and Statistical Modeling Time Series Forecasting Model evaluation, tuning, and optimization Python (Advanced), SQL (Advanced), PySpark, REST APIs, Microservices Architecture, Git and Version Control, Software Design Patterns Generative AI Skills: Large Language Models (LLMs) Prompt Engineering Retrieval-Augmented Generation (RAG) Agentic AI frameworks (AutoGen, LangGraph, CrewAI, Semantic Kernel) AI Orchestration and Multi-Agent Systems Vector Databases LLMOps and AI Governance Visualization Skills Know-how of any visualization tools such as Power BI, Tableau Good storytelling skills to present the data in simple and meaningful manner Data Engineering Skills Strong skill in data analysis techniques to generate finding and insights by means of exploratory data analysis Good understanding of how to transform and connect the data of various types and forms Data extraction algorithm creations Build algorithms and prototypes Reformulation of existing frameworks to optimize their functioning. Data Flow Diagram (DFD) Creation, Technical Design Documentation, Pipeline Design Specifications Soft Skills: Self-motivated to find use cases, biz value. Problem solving and innovation Ability to interact with multiple stakeholders to gather the required knowledge of the business process and convey ideas. Good Say to do ratio Structured approach to problem solving Strong adherence to on time delivery JOB SPECIFICATIONS: Graduate Engineer – preferably in Electronics or computer science Minimum 7-10 years of experience in data Analytics and data science Proven ability to work Agentic AI platforms and tech stack Experience in large IT project implementation related to Supply Chain management, factory scheduling, big data lake architectures is a plus Proven track record of ability to ideate, develop unique solutions using data science Talent acquisition based on Nexperia vacancies is not appreciated. Nexperia job adverts are Nexperia copyright © material and the word Nexperia® is a registered trademark. D&I Statement As an equal-opportunity employer, Nexperia values diversity not just because it is the right thing to do but because diverse teams perform better. We are dedicated to being inclusive, and a proof point of this dedication is that we were the main partner of the very first Dutch Paralympic Team NL House during the Paris 2024 Paralympic Games. Our recruitment process is inclusive and accessible to all, and we consider all applicants fairly, as well as providing a safe work environment and reasonable adjustments where requested. In addition, we offer our colleagues the possibility to join employee resource groups such as the Pride Network Group or global and local Women's groups. Nexperia is committed to increasing women in management positions to 30% by 2030.