Top Machine Learning Jobs in Germany

Lead end-to-end enterprise sales in Financial Services for Cloudflight’s tech portfolio. Generate pipeline, engage executives, develop tailored solutions and proposals, close complex deals, and grow strategic accounts. Coordinate with delivery, architects, and partners (Microsoft, Databricks, AWS). Manage CRM, forecasting, and cross-sell/upsell activities across cloud, data, AI/ML, and custom software offerings.

Lead and expand a strategic financial-institution account across the DACH region. Build C-suite relationships, identify business challenges, develop tailored enterprise solutions, structure and negotiate multi-million-dollar SaaS deals, and execute joint business plans to achieve growth and profitability targets. Act as the client advocate internally, influence product strategy, collaborate across sales and delivery teams, and serve as a trusted advisor on analytics, fraud, risk, lending, and decisioning technologies. Travel may reach 50%.

Design and develop control architectures and advanced control algorithms for integrated electrical and automation systems. Lead subsystem integration for synchronized plant operation, modernize power management strategies, and implement diagnostics and predictive maintenance to improve reliability and performance.

The Data Scientist will design algorithms for insights, structure data, collaborate with machine learning engineers, and analyze datasets to improve workflow automation and product value.

Build, deploy, and scale Bayesian MMMs and econometric/time-series models to measure marketing impact. Engineer reproducible, production-grade model pipelines, automate validation and health monitoring, and translate model outputs into business decisions while partnering with marketing leadership.

Assess and evaluate AI-generated technical content, craft and answer advanced ML/AI questions, identify errors and hallucinations, rank responses by correctness and clarity, and provide precise feedback to improve model performance.

The Account Executive will leverage technical expertise in enterprise SaaS sales to drive revenue growth, build partnerships, and represent Neural Concept's technology in engineering sectors.

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

The AI Product Manager will drive the development of AI-powered applications, collaborating with engineering and design teams, conducting market research, and optimizing AI models to align with user needs.

As a Principal Software Engineer, you'll lead multiple teams in Risk Management, designing cloud-based solutions, mentoring engineers, and driving innovation.

Lead EMEAI Logistics operations, managing a team of 140+ logistics professionals to meet customer expectations and drive digital transformation. Develop logistics strategies to improve service and reduce costs while ensuring compliance with performance standards.

The role focuses on client consulting and delivering commercial excellence in the Life Sciences industry, managing multiple workstreams and stakeholder relationships.

Lead and scale Feedzai's EMEA partner ecosystem (GSIs, OEMs, acquirers, processors, hyperscalers, ISVs). Drive partner strategy, joint go-to-market, partner-sourced revenue, onboarding/enablement, KPIs and reporting, and support joint marketing and demand-generation activities.

Develop and integrate reinforcement learning agents into autonomous aerial systems, ensuring reliability and performance. Collaborate with teams and enhance the software stack while mentoring peers.

As Lead Systems Engineer, oversee integration of EO/IR sensing systems, manage technical suppliers, define requirements and ensure operational readiness.

Leads and develops a robotics and AI operations team, supports hiring, improves workflows, and coordinates teleoperation programs for humanoid and dual-arm robots. Owns project planning, timelines, resources, stakeholder communication, risk mitigation, delivery, and long-term roadmap development across engineering, software, AI, and product teams.

Lead Data, Analytics, AI, and GenAI presales activities for strategic enterprise opportunities. Facilitate discovery workshops, translate business needs into scalable architectures, lead RFP and RFI responses, and present solutions to executives. Design end-to-end AI and cloud architectures across Azure, GCP, Databricks, and open-source ecosystems. Advise on AI transformation use cases, roadmaps, governance, and implementation, while mentoring delivery teams and developing reusable frameworks, offerings, thought leadership, and customer success materials.

Build Solidgate’s new ML/AI function, developing production machine learning models, recommendation systems, and real-time transaction-routing decision systems. Own experimentation from ideation through A/B testing and deployment, engineer features from high-cardinality transactional data, integrate emerging AI technologies, and collaborate with Product, Engineering, and Data Platform teams on training and analytics pipelines.

Own day-to-day execution of the SAP partnership across technical, research, and commercial workstreams. Track commitments, coordinate engineering and research capacity, support joint scoping, co-selling, pricing, packaging, and commercial terms, and maintain accurate partnership records. Onboard SAP stakeholders, identify stalled initiatives, escalate delivery-capacity risks, and help build scalable partnership processes, playbooks, and templates.

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.

Lead architecture and execution of data platforms and LLM-powered products: design and scale data pipelines, integrate and deploy models, define engineering standards (testing, evals, observability, SLOs), mentor engineers, drive cross-functional delivery, and optimize reliability, cost, and product outcomes for enterprise customers.

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 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.

Build and deploy production ML systems for large-scale ecommerce search and recommendations using text, image, and multimodal approaches. Tune and integrate LLMs and transformer models, develop end-to-end visual solutions, improve business KPIs through experimentation, and collaborate across teams to productize and scale ML capabilities.

Build production-grade ML and MLOps infrastructure for cloud-native environments. Responsibilities include orchestrating Kubeflow pipelines, training and fine-tuning GPU-based models and LLMs, tracking experiments with MLflow, developing Python tooling, processing large datasets, and maintaining CI/CD, testing, security, and clean-code standards within Kubernetes.