Top Machine Learning Jobs in Berlin

Support and improve ML/LLMOps and AI-agent infrastructure: evaluate LLM frameworks and APIs, build RAG pipelines, design agent evaluation systems, automate ML/data pipelines, and document findings.

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.

Seeking a Senior Software Engineer (Machine Learning) to develop scalable backend solutions for ML models, collaborating with cross-functional teams and optimizing workflows.

Design, build, and deploy production-grade ML systems and data pipelines in Databricks. Perform EDA, statistical A/B testing, feature engineering, and predictive modeling. Define metrics with stakeholders, produce dashboards and visualizations, and collaborate with product and engineering to drive KPI improvements while applying software engineering best practices.

The AI / Machine Learning Researcher will conduct applied research, develop prototypes, and work with data to create AI-driven features related to home design.

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

Build and own end-to-end frontend and backend ML platform features, collaborate with product and research to productionize model and agent capabilities, and design scalable, reliable, and secure data science tools.

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.

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.

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.

The Senior Data Engineer designs, maintains, and optimizes ML applications and data pipelines, ensuring compliance and quality while mentoring junior engineers.

As a Senior Data Engineer, you will design and maintain ML applications, manage workflows, build data pipelines, and mentor junior engineers within a global team.