Senior Engineer Data Science

Your Role

Key responsibilities in your new role

• Model Development & Delivery
• Design, build, and validate ML/DL models across diverse domains(computer vision, NLP, predictive analytics, anomaly detection)
• Oversee and drive the full model lifecycle: problem framing, data engineering, experimentation, evaluation, and deployment — collaborating with engineers and analysts for implementation
• Apply rigorous statistical methods, hypothesis testing, and feature engineering to produce production-quality models
• Monitor deployed AI models against KPIs; detect performance drift and trigger calibration, re-training, or architectural updates
• Benchmark models and deliver structured evaluation reports to technical and business stakeholders
• Agentic AI & Generative AI Application
• Develop and maintain LLM-powered solutions including RAG pipelines, AI agents, and multi-step tool-calling workflows
• Integrate Gen AI capabilities into business processes, automating knowledge retrieval, reporting, and decision-support workflows
• Evaluate and select appropriate foundation models, embedding strategies, and orchestration frameworks for production use
• Deployment, Scaling & Cross-Functional Collaboration
• Lead deployment readiness and cross-site scaling of AI solutions; standardize workflows for consistent execution
• Collaborate with operations, engineering, and IT teams to align solutions with business needs and system constraints
• Responsible for document findings, model decisions, and architecture clearly for both technical and executive audiences
• Share knowledge through tech talks, internal publications, and peer reviews to elevate team AI maturity
  
  
  

Your Profile

Qualifications And Skills To Help You Succeed

• Ph.D. or Master's in Computer Science, Data Science, Statistics, Mathematics, or a related Natural Science field is preferred
• Minimum 3–5 years of hands-on experience in data science, ML engineering, or applied AI research
• Demonstrated experience supporting models in a production or pre-production environment
• Proficient in Python and SQL; strong coding standards and documentation discipline
• ML/DL frameworks: Scikit-learn, TensorFlow, Keras, and/or PyTorch
• Solid grounding in statistics, model evaluation, hyper-parameter tuning, and feature engineering
• Experience with NLP, text mining, and structured/unstructured data processing
• Knowledge of version control with Git; familiarity with CI/CD principles for model delivery
• Exposure to GPU/HPC environments and containerization concepts (e.g., Kubernetes)
• Working knowledge of Large Language Models (LLMs) — model selection, prompt engineering, context management, and fine-tuning considerations
• Experience in designing and implementing AI agents: multi-step reasoning, tool/function calling, and autonomous task orchestration
• Strong communicator with the ability to translate complex AI concepts for non-technical stakeholders
• High ownership mentality with ability to manage multiple deliverables and meet project milestones
• Collaborative team player, effective across data science, engineering, and business functions
  
  

#WeAreIn for driving decarbonization and digitalization.

As a global leader in semiconductor solutions in power systems and IoT, Infineon enables game-changing solutions for green and efficient energy, clean and safe mobility, as well as smart and secure IoT. Together, we drive innovation and customer success, while caring for our people and empowering them to reach ambitious goals. Be a part of making life easier, safer and greener.

Are you in?

We are on a journey to create the best Infineon for everyone.

This means we embrace diversity and inclusion and welcome everyone for who they are. At Infineon, we offer a working environment characterized by trust, openness, respect and tolerance and are committed to give all applicants and employees equal opportunities. We base our recruiting decisions on the applicant´s experience and skills. Learn more about our various contact channels.

Please let your recruiter know if they need to pay special attention to something in order to enable your participation in the interview process.