Über
We are seeking an experienced Artificial Intelligence / Machine Learning Engineer to support the design, development, and implementation of advanced AI-driven solutions. This role requires strong hands-on experience building and deploying machine learning models, applying AI technologies to real-world problems, and collaborating with cross-functional teams to deliver scalable solutions.
The ideal candidate will have a strong technical background in AI development, machine learning, and data-driven application design, with the ability to quickly assess business needs and translate them into practical AI solutions.
Key Responsibilities Develop proof-of-concepts (POCs) and production-ready AI applications. Design, develop, and deploy AI and machine learning models to solve complex business problems. Build and optimize predictive models, NLP models, and data-driven algorithms. Collaborate with engineering, product, and data teams to integrate AI solutions into existing platforms and applications. Evaluate datasets, perform feature engineering, and prepare data for model training and testing. Monitor model performance and continuously improve accuracy and scalability. Document models, architecture, and implementation approaches for maintainability and scalability. Provide technical guidance on AI strategy, architecture, and best practices. Required Qualifications
Strong, demonstrable experience in Artificial Intelligence development and implementation. Proven machine learning experience with practical, real-world application. Experience building, training, and deploying machine learning models in production environments. Strong programming skills in Python, R, or similar languages. Experience with ML frameworks Experience working with large datasets and data pipelines. Knowledge of model evaluation, optimization, and performance tuning. Strong analytical and problem-solving skills. Preferred Qualifications
Experience with Natural Language Processing (NLP), Generative AI, or deep learning models. Experience integrating AI with cloud platforms such as AWS, Azure, or Google Cloud. Familiarity with MLOps practices, model deployment pipelines, and containerization tools (Docker, Kubernetes). Experience building AI-powered applications, automation tools, or intelligent workflows.
Sprachkenntnisse
- English
Hinweis für Nutzer
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