Top Machine Learning Jobs in Munich

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

The AI Research Scientist will conduct research to develop new ML models, lead projects, and explore data sources while collaborating with a global team.

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

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

As a Senior Research Engineer, you will manage data lifecycle for researchers, build a human-centric data lake, and enhance model performance through high-quality datasets in an AI-driven environment.

The Senior Quality Operations Engineer will manage quality systems, ensure compliance with regulations, oversee audits, and optimize workflows in medical technology.

As a ML Performance Engineer, optimize model training and inference pipelines, develop efficient solutions, and promote best practices in computing resources.

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 Technical Writer will create customer-facing documentation, collaborate with teams to improve user experience, and establish writing best practices.

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.

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

Lead the AI/ML team to develop innovative solutions for environmental challenges, emphasizing strategic guidance, collaboration, and team empowerment.

Lead the design of machine learning systems, mentor engineers, and ensure reliable data processing in a SaaS environment while driving operational excellence.

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

Lead the development of machine learning infrastructure for cybersecurity, driving production ML systems from experimentation to deployment, while mentoring junior engineers.

Lead the design and deployment of advanced ML/AI models for customer service, mentor teams, and drive research vision at Zendesk.

Responsible for developing AI/ML solutions in cloud-based environments, optimizing pipelines, integrating ML models, and mentoring junior staff.

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.

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

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 a Senior Software Engineer, you'll create advanced AI systems to improve developer productivity, integrate existing tools, and mentor junior engineers.

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 Big Data Engineer will architect and build data infrastructure, develop cloud-based processing pipelines, and ensure code quality for ML projects.