Ihre Aufgaben:
* Collect, clean, and preprocess structured and unstructured data from various source
* Perform exploratory data analysis to uncover trends and patterns
* Dvelop predictive and prescriptive models using machine learning and statistical techniques
* Design, develop, customize, optimize, and fine-tune algorithms tailored to specific use cases such as anomaly detection, predictive modeling, time-series forecasting, recommendation systems, text generation, summarization, information extraction, chatbots, AI agents, code generation, document analysis, sentiment analysis, data analysis, etc.
* Collaborate with developers and stakeholders to integrate statistical models, LLMs and classical AI techniques into end-user applications, focusing on user experience, and real-time performance
End-to-End Pipeline Development:
* Build and maintain production-ready end-to-end pipelines, including data ingestion, preprocessing, training, evaluation, deployment, and monitoring
* Automate workflows using DevOps / MLOps best practices to ensure scalability and efficience
* Collaborate with other developers to deploy models at scale, using cloud-based infrastructure (AWS, Azure)
* Implement continuous monitoring and refining strategies for deployed models, using feedback loops and e.g. incremental fine-tuning to ensure ongoing accuracy and reliability; address drifts and biases as they arise.
* Apply software development best practices, including writing unit tests, configuring CI/CD pipelines, containerizing applications, prompt engineering and setting up APIs, ensure robust logging, experiment tracking, and model monitoring
Ihre Qualifikationen:
* Deally Master’s degree in data science, computer science, statistics, or related quantitative field
* Experience in data science or a related role
* Experience in AI/ML engineering, with exposure to both classical machine learning methods and language model-based applications
* Advanced proficiency in Python, data analytics, statistical modeling and ML/AI. Experience with leading ML/AI frameworks and tools, with hands-on experience in designing and implementing end-to-end GenAI pipelines
* Strong understanding of DevOps / MLOps tools and practices, including version control, CI/CD pipelines, containerization, orchestration, Infrastructure as Code, automated deployment
* Experience in deploying statistical models, LLM and other AI models with cloud platforms (AWS, Azure) for robust and scalable productizations
* Expertise in working with structured and unstructured data, including data cleaning, feature engineering with data stores like vector, relational, NoSQL databases and data lakes through APIs
* Effective communication in English, problem-solving and innovative mindset, adaptability, curiosity, responsibility
Ihre Vorteile:
* 30 days leave per year
* A highly motivated team and an open way of communication
* You will work in an international environment
* We will give you valuable tips and feedback on your application documents and interviews