Senior Machine Learning Engineer

As a Senior Machine Learning Engineer – Language Technologies, you will design, build, and deploy natural language processing (NLP) and machine learning solutions that address complex business and technical challenges. You will work with large language models (LLMs) and develop scalable solutions for production environments, both on-premises and across cloud platforms.Working in an international environment, you will have the opportunity to use cutting-edge technologies to develop innovative solutions with global impact.Key ResponsibilitiesDesign, implement, and deploy scalable natural language processing and machine learning solutions.Work with large language models (LLMs) in production environments to enable near real-time solutions.Build and maintain machine learning pipelines and deploy models to improve the accuracy and efficiency of various stages within our processes.Develop text and speech solutions for both real-time data streams and batch-processing environments.Extend prototypes into robust, scalable, production-ready solutions.Contribute to internal development processes, technical standards, and engineering best practices.Provide technical guidance and coaching to colleagues, supporting their development and enabling them to succeed.Skill and Experience:Strong experience in natural language processing (NLP), natural language understanding (NLU), machine learning, software engineering, or a related technical or academic environment.Hands-on experience with machine learning frameworks and libraries such as Hugging Face, Keras, PyTorch, Scikit-learn, or similar technologies.Strong proficiency in Python and associated libraries, as well as Unix/Linux scripting.Practical experience across the machine learning lifecycle, including model development, training, deployment, monitoring, and optimization, particularly within the text and/or speech domain.Strong software engineering skills with a good understanding of data structures, data modelling, and software architecture.Experience managing and supporting large-scale machine learning applications in production environments.Experience with one or more major cloud platforms such as AWS, Microsoft Azure, or Google Cloud Platform (GCP) would be advantageous.