Top Machine Learning Jobs in Germany

Extract, curate, and ensure high-quality structured and unstructured oncology clinical data from EHRs. Develop and update curation instructions and capture forms, support QA processes, pilot new extraction approaches, contribute insights to product and ML/LLM-enabled curation, and collaborate with cross-functional teams to maintain and deliver high-quality datasets for research.

CrowdStrike seeks a Senior Intelligence Analyst to provide threat intelligence and digital risk monitoring, collaborating with teams to deliver customer-focused solutions and presentations, while maintaining customer relationships.

Sell Zscaler Zero Trust Branch solutions across DACH, owning regional quota, building account-based strategies, partnering with solution engineers, engaging C-suite and technical stakeholders to close complex deals for SD-WAN, data security, and advanced network products.

Design and productionize ML systems for advertising using multimodal data (image, video, audio, text, structured). Improve MLOps and data platforms, build scalable data pipelines, monitor models, collaborate cross-functionally, and drive team processes and product impact.

Design, build, and productionize machine learning solutions on AWS. Work end-to-end from data exploration, feature engineering, modeling, and evaluation to packaging, deploying, monitoring, and iterating models (including LLM/GenAI workflows). Collaborate with engineers, product partners, and data scientists to deliver reliable, reproducible ML systems and move prototypes into scalable production.

As a C++ Engineer, you will develop machine learning features, integrate models, maintain SDKs, and collaborate across teams for software performance and enhancements.

Lead technical design and build production-grade agentic AI systems for logistics, including LLM-based agents, RAG pipelines, and HERE API integrations. Own end-to-end delivery from prototyping to production, write high-quality Python/TypeScript code, design distributed geospatial systems, improve reliability and observability, and collaborate with product and domain experts to operationalize scalable AI solutions.

Design, develop, and validate state-of-the-art generative and self-supervised ML models for molecular and ligand-based drug design. Apply diffusion/flow-based and representation learning approaches, build predictive models (e.g., binding affinity), work with large proprietary and external datasets, collaborate with computational biology and chemistry teams, and translate research into applied drug discovery solutions while contributing to publications and scientific engagement.

Lead the Weaviate Database product: own roadmap and strategy, translate customer and research insights into features across schema, storage, replication, and search quality, coordinate cross-functional teams, drive developer adoption, and measure feature outcomes post-release.

Lead and grow the engineering organization to improve delivery predictability, quality, and cross-functional alignment. Drive adoption of AI-assisted software development, improve planning and execution, coach engineers and future leaders, and strengthen collaboration with Product, ML, Clinical, and Regulatory teams.

The intern will assist in AI research focused on semantic structure extraction and content generation, supporting data analysis, experiments, and documentation.

Lead end-to-end ML product roadmaps and initiatives (e.g., Attachment Matcher, Transaction Categorizer). Collaborate with data scientists, engineers, and stakeholders to define, deliver, and monitor ML solutions that drive measurable business value for SMEs across Qonto's platform.

Lead and grow a team of data analysts in AdTech, shifting them from reactive reporting to proactive, revenue-focused partners. Own delivery processes, prioritize high-ROI projects, manage Director-level stakeholders, translate Ads strategy into measurable goals, ensure technical QA of SQL and dashboards, and operationalize ML models with data science partners to maximize ad yield and vendor ROI.

Lead AI-enabled computational pathology and multimodal biomarker development for oncology programs. Drive biomarker strategy, cross-functional discovery, proof-of-concept studies, data integration (imaging, genomics, proteomics, blood, clinical), validation, and regulatory support, and scale reusable platform capabilities across drug development.

Lead AI-driven computational pathology and multimodal biomarker programs for oncology/biopharma. Provide strategic scientific leadership, build and direct cross-functional teams, deliver reusable biomarker platforms, oversee translational studies and validation, support regulatory readiness, and act as an external scientific ambassador to enable patient selection and accelerate drug development.

Lead development and implementation of AI-enabled computational pathology and multimodal biomarkers for oncology. Drive biomarker discovery, integrate tissue/imaging/genomic/clinical data, support analytical validation, regulatory submissions, vendor selection, and cross-functional project leadership to inform patient selection and clinical decision-making.

Perform remote, part-time data tasks to improve German AI content, including data collection, evaluation, annotation, pairwise comparisons, counting tasks, and object tagging across audio, video, and images.

Research and investigate global fraud trends using BioCatch data and external sources. Produce data-driven insights, visualizations, written thought leadership, dashboards, and presentations. Build repositories and automate analysis workflows while applying fraud expertise and AI tools to validate findings and support sales and marketing.

Lead and grow a multidisciplinary digital toxicology team in Frankfurt to develop AI/ML and QST models, integrate computational tools across preclinical safety workflows, build AI-ready data foundations, modernize the digital toxicology toolkit, and drive cross-functional adoption and regulatory-aligned in silico approaches.

Lead the end-to-end search experience: improve relevance, discovery, ranking, and UX across platforms. Collaborate with data science/ML to define metrics and experiments, prioritize a roadmap, and optimize search infrastructure, autocomplete, filters, and zero-results handling for complex health-related journeys.

Analyze and manage customer credit risk for BNPL products across Europe, optimize consumer portfolios via business rules, improve data analysis and reporting, support risk steering platform development, and advise Key Account Management on risk measures.

Lead redesign and development of B2B underwriting models, scorecards and decision engines; improve data analysis and processes; build multi-country credit frameworks; partner with Data Science to deploy ML credit models; enhance reporting and risk KPIs; collaborate with cross-functional teams to support B2B product expansion.

Manage customer credit risk for BNPL products across Europe by analyzing consumer portfolios, optimizing business rules, improving data analysis and processes, collaborating on model changes, advising Key Account Management on risk measures, and supporting risk steering platforms and BI/reporting enhancements.

Lead technical discovery and early development of an action-recognition CV product for retail: design experiments, build end-to-end video ML pipelines, set up annotation workflows, prototype and evaluate models, optimize precision/recall and latency, and provide technical leadership across product and engineering.

Lead business analytics projects partnering with ABB business areas: design data migration, integration, validation, reporting and governance; manage cloud analytics platforms, vendors and infrastructure; pilot AI/ML solutions and ensure alignment with business objectives and controls.