Top Machine Learning Jobs in Germany

Guide customers through Zscaler’s Zero Trust adoption as a post-sales technical contact. Build stakeholder relationships, provide technical guidance and best practices, develop integration strategies, coordinate complex escalations, identify adoption risks, and collaborate on mitigation plans. The role also contributes to customer success playbooks and best-practice resources while advising on cloud, networking, security, and AI-powered solutions.

Conduct research and development in future flight operations, including ground operations, trajectory-based operations, knowledge-based engineering, accessibility, and artificial intelligence. Support simulator maintenance and visitor tours while collaborating with international researchers, labs, stakeholders, and customers. The role requires student status, English fluency, German work authorization, flexible availability for 20 hours weekly, and the ability to contribute proactively to interdisciplinary projects.

Apply machine learning and generative AI systems to extract clinically relevant information from oncology records. Validate AI-generated datasets, analyze model and dataset performance, define training and evaluation requirements, support data product development, and collaborate with clinicians, researchers, engineers, and international stakeholders to productionize and monitor models used in cancer research.

Develops and integrates radiating components and passive radiation-pattern structures for multiband base-station antennas. Responsibilities include 3D and 2D electromagnetic simulation, prototype RF measurements, performance optimization, troubleshooting, technical documentation, and supporting the product lifecycle through mass production. The role collaborates with international cross-functional teams and requires relocation to Rosenheim, Germany.

Serve as a strategic presales advisor for German medium enterprises, translating HR requirements into tailored Workday HCM demonstrations and business cases. Lead discovery, explain AI and trustworthy data practices, address DACH compliance and works council considerations, and collaborate with account executives, value managers, and services teams throughout sales cycles. Maintain knowledge of regional market trends, competitors, and the Workday product roadmap while presenting solutions to HR and executive stakeholders.

Develop and improve product recommendation systems for Redcare Pharmacy’s webshop and app. Responsibilities include customer and product data analysis, feature engineering, machine learning model development, A/B testing, statistical evaluation, and productionization. The role involves end-to-end data science initiatives, including monitoring and continuous improvement, while collaborating with product managers, ML engineers, data engineers, MLOps, and domain experts.

Develop and improve product recommendation models for Redcare Pharmacy’s webshop and app. Analyze customer and product data, engineer features, conduct A/B tests, define success metrics, and interpret experimental results. Partner with product, engineering, data, and domain teams across the full data science lifecycle, including exploration, experimentation, production deployment, monitoring, and continuous model improvement.

Develop and improve product recommendation models for Redcare Pharmacy’s webshop and app. Analyze customer and product data, engineer features, apply machine learning, and design A/B tests to measure impact. Collaborate with product, engineering, and domain teams across the full data science lifecycle, including experimentation, productionization, monitoring, and continuous improvement.

Own the vision, roadmap, and backlog for SEO, product content, metadata, media, and discoverability platforms. Lead development of scalable backend capabilities, faceted navigation, structured data, crawling, indexing, automation, and AI-supported enrichment. Collaborate with SEO, content, shop operations, product, data, engineering, and business stakeholders. Manage agile delivery, ceremonies, stakeholder alignment, platform adoption, metadata quality, operational efficiency, and discoverability KPIs.

Develop forecasting and analytics solutions for Workforce Management, including scheduling and intraday forecasts, capacity planning, KPI dashboards, root cause analysis, SLA improvement, cost optimization, and data pipeline enhancement. The role requires influencing senior stakeholders and translating data-driven insights into operational decisions.

Design, build, evaluate, and deploy production AI systems for enterprise and digital-native customers. The role involves coding, prototyping, integrations, debugging, reliability, observability, security, governance, and optimization across AI application stacks. The engineer translates customer needs into architectures and implementation plans, guides systems from prototype to production, supports adoption and scale, and creates reusable tooling and deployment guidance while providing product feedback.

Build and ship production software for millions of users across TypeScript, Python, DevOps, or AI tracks. Own problems from concept through deployment, use AI tools responsibly, debug root causes, and improve system reliability, performance, and failure handling. Depending on the track, responsibilities include web and mobile features, rewards and payment services, CI/CD infrastructure, deployments, AI tooling, LLM-powered features, and internal automation.

Lead GetYourGuide’s design systems strategy, team, governance, and capabilities across product, design, engineering, and business functions. Build scalable design patterns and processes, incorporate automation and AI-assisted tooling, and advance accessibility, localization, generative UI, adaptive theming, and personalization. Guide work from strategy through implementation while improving collaboration, efficiency, consistency, and product quality across a global technology organization.

Develops power system analysis and optimization algorithms for power grid applications. Responsibilities include modeling real-world power system problems, designing computational experiments, developing reproducible software, collaborating with researchers and product teams, integrating algorithms into production applications, and communicating results through publications, patents, technical reports, design documents, and notebooks.

Develop and improve fraud, credit, and insolvency risk models and embedding models across the full machine learning lifecycle. Responsibilities include analyzing complex datasets, researching transformer-based methods, designing and training models, deploying them into real-time systems, monitoring performance, and translating findings into measurable business impact. The role requires collaboration with operations and internal tool developers while balancing fraud prevention with positive customer experiences.

Lead product vision and discovery for a genomics-driven diagnostic and personalization platform. Validate hypotheses with patients, clinicians, and partners; translate research into product specs; coordinate labs and data providers; partner with engineers and researchers to build AI prototypes; shape data, regulatory, and GTM strategy while making core product and architectural decisions.

Build core components of a diagnostic and personalization platform: backend data pipelines, frontends, services for genomic data ingestion, ML model integration, APIs, and cloud infrastructure. Collaborate with product and ML teams, iterate on prototypes and MVPs, and make architectural decisions supporting scalability and reliability.

Leads strategic Professional Services sales and advisory activities across the DACH region. Positions Workday’s AI, extensibility, analytics, and transformation capabilities; conducts consultative discovery; aligns Global Systems Integrator partners; negotiates services agreements and statements of work; manages forecasts; and builds executive customer relationships. Requires enterprise software or digital transformation consulting experience, change management expertise, complex sales success, German and English fluency, and travel up to 35%.

Defines success metrics and evaluation strategies for ML products, including simulations, benchmarks, guardrails, and structural consistency checks. Partners with Product Owners and Data Science teams to translate business questions into analytical problems and model results into business decisions. Builds rapid prototypes, offline evaluations, self-service analytics, and AI-assisted tools while establishing evaluation standards across product teams.

As a Research Engineer, you'll develop and manage data systems for text-to-speech projects and enhance machine learning models using innovative strategies.

Lead the vision, roadmap, architecture, and execution strategy for a centralized machine learning platform at a digital bank. Own enterprise MLOps infrastructure, model evaluation, monitoring, governance, and high-volume real-time decisioning for fraud, credit risk, and operations. Partner with engineering, data science, security, legal, and regulatory stakeholders while mentoring product managers and establishing platform standards.

Student intern developing AI-focused customer solutions with SAP. Responsibilities include discovering and architecting AI use cases, implementing solutions across frontend, backend, databases, integrations, and machine learning, researching agent-related technologies, and collaborating with international teams and customers. The role supports growth toward full-stack development through hands-on projects, mentorship, and exposure to business applications of emerging technologies.

Develop and scale LLM-powered virtual assistants and agentic support systems. Build autonomous resolution and decisioning models, implement RAG and other GenAI techniques, establish evaluation and safety guardrails, and deploy models in low-latency production environments. Collaborate with engineering, product, decision science, and support teams to improve automation, containment, and customer satisfaction through experimentation and data-driven solutions.

Build Solidgate’s ML/AI function from the ground up, developing real-time payment routing models and production pipelines. Own the full ML lifecycle from experimentation and A/B testing through deployment, while solving modeling challenges involving large-scale transactional data. Partner with Product, Engineering, and Data Platform teams to deliver measurable improvements in conversion, approval rates, losses, and revenue.

Lead an international risk analytics team focused on credit solvency and fraud risk. Drive data-driven risk strategies, monitoring, reporting, pricing insights, process improvements, and advanced analytics. Enable machine-learning-based risk decision models, collaborate with Risk, Data Science, Pricing, Finance, Sales, and Operations teams, and represent Risk Analytics in strategic projects.