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

Job description

• Development, deployment, and maintenance of ML and AI artifacts within an agile product development team in the emerging AI unit.
• Design, development, and maintenance of machine learning solutions in a DevOps environment.
• Contribute throughout the entire lifecycle—from the concept phase through deployment—and collaborate closely with cross-functional teams to deliver robust, data-driven solutions.

Tasks

• Design and implementation of RAG systems (e.g., LLMs) to support AI responses based on corporate data.
• Evaluation and integration of AI models (e.g., LLMs) while ensuring optimal performance.
• Optimization of agent workflows and AI agents for production use cases.
• Testing and optimizing system prompts and few-shot examples to ensure accurate and reliable AI outputs.
• Performance evaluation of machine learning and AI models using appropriate metrics and techniques, as well as continuous iteration and improvement.
• Collaborate with platform teams, data engineers, data scientists, and other stakeholders to integrate machine learning solutions into existing systems and processes.
• Participate in code reviews, testing, and debugging to ensure the quality and reliability of machine learning solutions.
• Development of multi-agent systems and equipping AI models with function/tool-calling capabilities.
• Quick problem-solving.

Requirements

• Strong problem-solving and analytical skills, with the ability to think critically and tackle complex challenges.
• Excellent communication and collaboration skills, with the ability to work effectively with cross-functional teams and stakeholders at all levels of the organization.
• Ability to effectively manage personal workloads, prioritize tasks, manage time, and deliver high-quality results on time.
• A lifelong learning approach driven by a passion for staying up to date with the latest developments in machine learning and artificial intelligence.
• Attention to detail and a commitment to producing high-quality, reliable, and maintainable machine learning solutions.
• A bachelor's or master's degree in data science, computer science, mathematics, or a related field.
• Proven programming skills in Python, with experience in machine learning libraries such as scikit-learn and xgboost, or frameworks such as TensorFlow and PyTorch.
• Strong knowledge of agile workflows for AI agents, LLM orchestration frameworks, and deep learning model architectures.
• In-depth knowledge of MLOps, including CI/CD pipelines, monitoring, and automated testing of ML models.
• Practical experience with AI frameworks and services such as Azure OpenAI, Bedrock, or Databricks.
• Preferred: Machine learning certification.
• Preferred: Relevant experience with reinforcement learning and RL training using LangGraph.
• Preferred: Familiarity with version control systems (e.g., Git) and cloud-based development environments.