Top Machine Learning Jobs in Germany

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

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.

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.

Internship focused on enhancing ML/LLMOps and AI agent infrastructure within AWS: evaluating LLM frameworks, building RAG pipelines, automating model evaluation/deployment, documenting findings, and contributing to ML/data pipelines.

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.

As an intern, you will develop machine learning algorithms and prototypes, working closely with a team of scientists and engineers.

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

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.

Lead and grow an ML engineering team to build, operate, and maintain production-grade ML systems (recommenders, search). Define quality standards, collaborate with product and data teams, and remain hands-on to guide architecture and delivery for business impact.

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.

Develop and scale neural networks for source code tasks, create and improve methods for code generation, editing, and agent-based workflows, mentor colleagues, and produce publishable ML research results.

The Senior AI Engineer will design scalable AI systems, focusing on LLM-powered agents and automation, optimizing delivery operations globally.

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

Lead and mentor a team of Applied Scientists and AI/ML Engineers to design and deliver production-grade AI solutions across structured CRM and unstructured data. Drive technical strategy for agentic workflows, RAG/vector DB systems, and real-time reasoning. Partner with AI Platform on LLMOps and cloud infrastructure, act as a technical authority, and contribute as a high-impact individual contributor to ship customer-focused AI products.

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.

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 Applied AI Engineer will onboard clients on Mistral AI products, manage complex integrations, and drive technological transformations through collaboration with stakeholders.

Lead the development of AI/ML systems for real-time applications, mentor teams, optimize performance, and contribute to the AI/ML community.

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

The ML/AI Engineer will benchmark GPU platforms for AI workloads, analyze GPU performance, optimize ML workloads, and develop performance visualization tools.

As a Senior AI/ML Engineer at SumUp, you will develop and deploy AI-driven solutions, manage ML infrastructure, and collaborate across teams to enhance customer experience and automate support services.

As a Machine Learning Researcher, collaborate with scientists and engineers to apply ML techniques in stellarator design, integrating solutions from prototyping to deployment, and establishing best practices for the field.