Top Machine Learning Jobs in Hamburg

The role involves designing and testing AI solutions, managing research projects, collaborating with teams, and introducing new ML concepts for product development.

The AI Content Evaluator will review and assess content for alignment with guidelines, ensuring quality and consistency in annotation. Responsibilities include evaluating various content types, applying structured criteria, and adhering to project guidelines.

Responsible for developing backend AI features, integrating machine learning models, building data pipelines, and maintaining AI services within a retail ecosystem.

The Pricing Advisory professional will assist clients in enhancing pricing strategies through consultation, model development, implementation support, and training sessions, while managing stakeholder relationships and navigating challenges in pricing sophistication.

Lead developer-facing work on advanced real-time rendering and neural graphics: optimize GPU/CPU performance, develop and tune neural rendering and AI models, collaborate with AAA studios and NVIDIA architecture/driver teams, build demos, publish and present research.

As a Senior Forward Deployed Engineer, you'll deliver AI solutions, engage with customers, and lead project lifecycles, including deployment and integration.

Lead the Voice team at Rasa, focusing on mentoring engineers, driving processes, and delivering voice features while maintaining strong communication and async practices.

This role involves enhancing a product through computer vision and deep learning, driving document parsing, improving quality metrics, and mentoring team members.

Nebius seeks a Senior ML Engineer for AI R&D focusing on applied research in reinforcement learning and agent training, requiring deep expertise in machine learning and software engineering.

Design and scale predictive ML systems for VIS.X, taking end-to-end ownership of various high-impact ML initiatives and shaping the ML architecture.

This internship focuses on designing solutions for secure data preparation in ML workflows, ensuring data privacy while maintaining model performance. Interns will prototype methods using advanced technologies like Trusted Execution Environments and contribute to academic publications.

Seeking a Senior/Lead Machine Learning Engineer with expertise in inference optimization, model acceleration, and high-performance systems for developing real-time multimodal models.

The Senior Infrastructure Engineer will design and maintain AWS infrastructure for AI/ML workloads, focusing on deployment, security, and collaboration with ML teams.

The Machine Learning Engineer will develop high-performance algorithms for retail decision-making, optimizing solutions and supporting data scientists in applying these algorithms effectively.

The Senior Machine Learning Engineer will architect and deploy recommendation systems, leverage large-scale data, develop machine learning models, and collaborate with engineering teams to optimize solutions and improve key business metrics.

The Senior AI/ML Engineer at Nansen will develop AI models for blockchain data analysis, collaborating with teams to enhance platform capabilities and mentor junior engineers.

End-to-end delivery of ML-powered services, involving research, prototyping, production, and operations. Collaborate on product requirements while maintaining high quality and operational excellence.

Lead the Applied AI Team in developing and deploying ML systems for clinical care, mentoring engineers, and driving initiatives across the AI stack.

Own and drive ML solutions for clinical care at scale, including LLM fine-tuning and production deployment, collaborating across teams.

The AI/ML Engineer will develop and implement ML systems for secure-code understanding, manage infrastructure for LLMs, optimize models, and conduct research.

Develop and maintain AI and ML algorithms, create data pipelines, collaborate with cross-functional teams, and implement solutions for business requirements.