(Senior) Machine Learning Engineer

at  ATOSS Software SE

YOUR CAPABILITIES:

• You’re holding a master’s degree in Computer Science, Engineering, or a closely related field
• You have at least 10 years of experiences in the Software Engineering and have at least 3 years of hands-on experience in the designing, developing, and delivering enterprise grade AI solutions (in complex software systems) to customers based on Artificial Intelligence
• You have strong programming skills in Python, R, or other relevant languages
• You have proficiency with data analysis and machine learning libraries (e.g., Scikit-learn, Pandas, NumPy)
• You have experience with cloud platforms (e.g., AWS, Azure, Google Cloud) and containerization (e.g., Docker, Kubernetes)
• You can demonstrate a robust foundation in technical knowledge, and you have problemsolving capabilities
• You are experienced in working with AI inference frameworks
• You have a deep understanding of NLP principles and techniques and bring a solid understanding of Transformer architectures, emphasizing Large Language Models (LLMs), Generative AI and proficiency in convolutional neural networks
• You are proficient in leveraging retrieval-augmented techniques for generative tasks
• You have the passion and ability to work in a fast-paced, dynamic environment
• You have strong organizational and project management skills
• You come with an open, proactive and innovative mindset

• Design, develop, and deploy scalable AI and machine learning models for internal and customer use cases
• Collaborate with cross-functional teams to integrate AI solutions into existing products.
• Collaborate with cross-functional teams to Integrate and manage AI models within the existing products as well as within various application environments
• Training and fine-tuning of AI models, focusing on achieving superior performance and precision
• Deploying on local GPU hardware, including profiling and optimization to ensure efficient execution of AI models
• Developing data processing pipelines and preparing data for NLP training
• Enhancing model performance by integrating external knowledge sources during the generation process
• Deploy AI models in production environments and ensure they are running efficiently
• Monitor and maintain AI systems to ensure they meet performance and reliability standards
• Implement logging, monitoring and alerting systems for AI solutions
• Collaborate with software engineers, data scientists, and other stakeholders to deliver high-quality AI solutions
• Provide technical guidance and mentorship to junior AI engineers and data scientists
• Contribute to code reviews, design discussions and technical documentation
• Work with large datasets to train and validate AI models
• Implement data preprocessing and augmentation techniques to enhance model performance
• Ensure data integrity and security throughout the AI development lifecycle
• Stay updated with the latest advancements in AI and machine learning technologies and conduct research to explore new techniques and methodologies
• Propose and implement innovative AI solutions to solve complex problems