Bei einer beruflichen Neuorientierung mit KI-Focus nachfolgend eine Liste von ausgewählten KI Jobs mit Aufgabengebiet und Anforderungen (Quelle ChatGPT):
| Job Title | What You Do / Focus | Key Skills / Requirements |
|---|---|---|
| Machine Learning Engineer | Build, train, deploy, and maintain ML models and systems | Strong programming (Python/Java/C++), ML frameworks (TensorFlow, PyTorch, etc.), understanding of algorithms, data pipelines |
| AI / Artificial Intelligence Engineer | More general AI system development, often combining multiple AI techniques | Similar to ML Engineer, but may include integrating models with systems, working on knowledge graphs, reasoning, etc. |
| Data Scientist | Analyze data, build predictive models, derive insights that drive decision-making | Statistics, data wrangling, ML modeling, communication & domain knowledge |
| Data Engineer | Build and maintain the data infrastructure (ETL, pipelines, data storage) used by ML/AI teams | Databases, big data tools (Spark, Hadoop), SQL, data architecture, cloud platforms |
| Research Scientist (AI / ML) | Work on advancing algorithms, publish papers, push the state of the art | Strong math, publications, deep understanding of theory, ability to prototype new approaches |
| Computer Vision Engineer | Focus specifically on image/video processing, object detection, segmentation, etc. | Expertise in CV methods, deep learning, OpenCV, domain-specific libraries |
| NLP / Language Model Engineer | Work on natural language processing, language models, chatbots, translation, etc. | Transformers, tokenization, embeddings, sequence models, linguistic knowledge |
| Robotics / Perception Engineer | Apply AI to robotics, sensors, perception, control systems | Robotics, sensor integration, control theory, real-time systems, ML/vision |
| AI Product Manager / AI Solutions Architect | Bridge business and technical sides: define AI products, roadmaps, translate requirements | Understanding of AI/ML, product strategy, stakeholder communication, feasibility assessment |
| AI Ethics / Responsible AI Specialist | Focus on fairness, bias, safety, explainability, compliance and governance aspects of AI systems | Ethics, policy, model interpretability, regulation, stakeholder engagement |
| AI Trainer / Prompt Engineer | (Especially with the rise of generative AI) crafting and refining prompts, managing human-in-the-loop data, training datasets | Understanding of models, experimentation, domain knowledge, prompt design |
| AI DevOps / MLOps Engineer | Ensure ML models are reliably deployed, monitored, scaled, and maintained in production | DevOps, CI/CD, containerization (Docker, Kubernetes), monitoring, automation |
| AI Consultant / AI Strategist | Work with clients / organizations to guide and implement AI adoption, strategy, use-case development |
Posted in: Recruitment
Posted on 27. April 2026