Top Machine Learning Jobs in Germany

As an AI Engineer focused on Machine Learning, you will develop AI solutions, participate in R&D projects, and improve enterprise practices.

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.

This role involves designing, maintaining, and optimizing data pipelines and machine learning processing. Responsibilities include project management, collaboration, and knowledge sharing within the organization.

The Machine Learning Research Engineer will enhance search technologies through model optimization, architecture building, data collaboration, and advanced research in AI, focusing on retrieval and ranking.

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.

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.

Research and develop AI/ML models for handwriting recognition and related technologies, collaborating with a multidisciplinary team to deliver innovative features.

You will ensure the reliability and efficiency of ML models, design evaluation systems, and drive performance improvements while collaborating closely with ML researchers.

Lead the architecture of AI/ML solutions on Azure, collaborating with enterprise clients to drive value. Establish MLOps best practices, provide technical leadership, and contribute to internal capabilities.

As a Senior Software Development Engineer at Mapbox, you'll lead product roadmap design, develop cloud applications, and integrate analytics solutions across teams, specializing in geospatial big-data analytics.

As a Senior Machine Learning Engineer, you will design and optimize forecasting algorithms, lead technical direction, and collaborate with teams to deliver scalable ML solutions in the energy sector.

The role involves designing and implementing machine learning capabilities for autonomous vehicles, focusing on perception, prediction, and planning systems. Engineers will work on software development processes from model creation to deployment, leveraging established products.

Design, build, and scale core infrastructure for machine learning models, manage production systems, and implement best practices in MLOps.

As a Senior Machine Learning Engineer, you'll deploy and optimize AI models, integrate new technologies, and collaborate on ML-powered product development.

The Robotics ML Engineer will build AI-first robotics projects and data pipelines, create educational content, and interact with customers to improve projects at Rerun.

As a Senior Data Engineer, you'll design scalable data pipelines, collaborate with engineers and product teams, and evolve the architecture to support growth in users and data.

As a Senior Geospatial Machine Learning Engineer, you will develop and improve algorithms for vegetation analysis, enhance existing products, and lead projects impacting wildfire risk management.

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 Senior Machine Learning Engineer will develop and maintain high-performance ML systems, enhance MLOps capabilities, and collaborate with cross-functional teams to improve marketplace performance.

Develop and maintain data-driven systems focusing on real-time feature engineering and MLOps practices while collaborating with Machine Learning and Data Science teams.