Top Machine Learning Jobs in Hamburg

As a Junior Pricing Manager, you will analyze sales prices, manage pricing strategies, collaborate on machine learning for optimization, and report performance KPIs across multiple markets.

Lead the AI compiler team to develop compilers for NextSilicon's platforms, leveraging expertise in large-scale compiler development and machine learning.

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

Seeking a seasoned data scientist to advance methodologies for cardiovascular health assessment, collaborating with medical experts and algorithmic team.

Join Motius' tech community as a freelancer, working on R&D projects in diverse tech fields like Software Engineering and Machine Learning.

Research and implement physics-informed AI algorithms, design workflows, supervise teams, collaborate with external institutes, and publish findings.

The Applied Scientist will solve impactful problems using deep learning models and statistical analysis, translating commercial goals into technical solutions.

The Staff Machine Learning Scientist will lead product vision through innovation, overseeing the R&D lifecycle, mentoring junior team members, maintaining research standards, and advancing AI technology in conversational systems.

Design, develop, and deploy scalable machine learning systems at Typeform, enhance AI capabilities, and collaborate across teams to drive innovation.

Lead high-scope AI and ML projects, focusing on Generative AI. Collaborate with cross-functional teams to design and implement solutions that enhance patient care.

Drive independent, high-impact research on frontier AI topics, publish findings, collaborate widely, and mentor new researchers in the field.

N-iX seeks a Data Engineer with MLOps experience to create scalable ML pipelines, deploy models, and contribute to best practices in data engineering and coding.

The Machine Learning Platform Engineer will manage cloud infrastructure, support AI researchers, and deploy models in production, focusing on MLOps and CI/CD practices.

As an AI/ML Specialist Solutions Architect, you will design scalable AI solutions, manage AI deployments, and collaborate with clients to enhance customer satisfaction.

The Staff Machine Learning Engineer will enhance Zendesk's search platform, deliver AI capabilities, mentor team members, and ensure service stability. Responsibilities include collaborating on feature development, technical discussions, and addressing challenges in retrieval systems and LLM technologies.

Lead the development of LLM-powered solutions, ensuring scalability and security. Oversee AI system integration and collaboration with various teams.

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.

The Senior ML Engineer will enhance fine-tuning methodologies, research inference optimization techniques, and re-implement LLM architectures focusing on distributed training and efficiency.

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.

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.

As a Senior Machine Learning Software Engineer, you'll develop high-performance systems for online inference and real-time feature engineering, optimize solutions in a collaborative team, and advance MLOps practices.

Develop and enhance machine learning systems for the marketplace, focusing on MLOps, high-performance data systems, and collaboration with diverse teams.

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

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.