Machine Learning Engineer (Full-Time) (f/m/d)

Tasks

• Development, deployment, and optimization of machine learning and AI solutions to address complex business challenges
• Development of multi-agent systems and equipping AI models with function- and tool-calling capabilities
• Design and implementation of RAG systems to support AI responses based on corporate data
• Evaluation and integration of AI models (e.g., LLMs), taking into account various size categories, to ensure optimal performance, cost-effectiveness, accuracy, and reliability
• Optimization of Agent-Based Workflows and AI Agents for Production Environments
• Testing and optimizing system prompts and few-shot examples to ensure accurate, cost-effective, and secure AI outputs
• Performance evaluation of machine learning and AI models using appropriate metrics, automation methods and techniques, as well as continuous iteration and improvement
• Collaborate with platform teams, data engineers, data scientists, and other stakeholders to integrate highly reliable machine learning solutions into existing systems and processes
• Participate in code reviews, testing, and debugging to ensure the quality and maintainability of machine learning solutions

Requirements

• Strong problem-solving and analytical skills, along with the ability to think critically and tackle complex challenges
• Excellent communication and collaboration skills to work effectively in cross-functional teams and with stakeholders at all levels of the organization
• Ability to effectively manage one's own workload, prioritize tasks, manage schedules, and deliver high-quality results on time
• A passion for continuous learning and an interest in staying up to date on the latest developments in machine learning and artificial intelligence
• Attention to detail and a commitment to producing high-quality, reliable, and maintainable code
• Bachelor's or Master's degree in Data Science, Computer Science, Mathematics/Engineering, or a related field
• Strong programming skills in Python with experience in machine learning libraries and frameworks such as TensorFlow or PyTorch
• Demonstrable experience working with large language models (LLMs)
• A solid understanding of AI agents and agent-based workflows, LLM orchestration frameworks, and reasoning
• Relevant professional experience in machine learning, data science, or a related field