Top Machine Learning Jobs in Germany

Supports development and validation of cloud-native telecommunications software and AI solutions for software engineering, knowledge management, automation, and developer productivity. Responsibilities include building scripts, tools, dashboards, prototypes, and proof-of-concept implementations; analyzing engineering data; supporting documentation and knowledge repositories; and participating in AI pilots, workshops, hackathons, and stakeholder collaboration.

Leads an international data science and AI team of up to eight members focused on commercial analytics and AI accelerators. Owns demand intake, prioritization, product strategy, model and data product delivery, and enterprise-scale ML/AI platform development. Partners with commercial, marketing, finance, and brand leaders to translate advanced analytics into business recommendations, revenue growth, and resource optimization. Requires executive communication, team-building, product management, and hands-on expertise in ML, LLMs, agentic workflows, cloud deployment, and pharma or healthcare analytics.

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.

Leads the Data Tribe, mentors team leads, and drives data-enabled business value across the company. Establishes data management, governance, integrity, and engineering guidelines; consults on data-driven practices; manages data infrastructure and analytics; supports ICT operations; and serves as Data Protection Coordinator for Engineering.

Own the full sales cycle for technically complex B2B deals involving APIs, on-premises deployments, and custom licensing. Manage multi-stakeholder negotiations, build strategic customer relationships, drive retention and expansion, and develop sales processes in an early-stage environment. Collaborate with engineering, research, product, solutions engineering, and legal teams while translating customer needs into product feedback.

Own end-to-end talent acquisition and headhunting for Arago’s technical hiring across France, North America, and Israel. Partner with the CEO, CTOs, and engineering leaders to define roles, source and close senior engineers, scientists, and technical leaders across hardware, optical, software, and research. Build proactive sourcing pipelines, improve interview processes and hiring standards, monitor pipeline health and hiring velocity, and communicate progress to leadership.

Identifies, designs, deploys, and sustains AI solutions within a Wind Engineering subsystem. Partners with engineering leaders to prioritize use cases, integrates AI into engineering workflows, ensures governance and cybersecurity compliance, drives adoption, and monitors solution performance and value. The role develops applications, agentic workflows, copilots, automation, predictive models, and knowledge systems while contributing reusable patterns and innovations to the broader AI community.

Leads the identification, design, deployment, integration, governance, adoption, and continuous improvement of AI solutions across a Wind Engineering subsystem. Partners with engineering and business leaders to prioritize AI use cases, build roadmaps, configure AI applications and agentic workflows, integrate solutions into engineering processes, validate outputs, ensure security and responsible AI compliance, educate teams, and monitor solution performance and business value.

Manage commercial customer accounts across an assigned Swiss territory, working remotely from Germany. Responsibilities include achieving sales quotas, developing new business, managing customer engagement and retention, enabling channel partners, maintaining pipeline and CRM accuracy, forecasting, delivering business reviews, coordinating with sales engineers, and attending customer or partner events. The role requires German and English fluency, sales experience, CRM knowledge, technical aptitude, strong organization, communication, and willingness to travel.

Develop statistical, machine learning, and predictive models to solve commercial and pricing business problems. Analyze large datasets with Python and SQL, use Databricks for advanced analytics, build Power BI dashboards and automated reports, and support AI tool deployment. Create workflow automation using PowerShell, PowerApps, or VBA while collaborating cross-functionally to translate business challenges into analytical solutions.

Partner with universities, research labs, and faculty to drive adoption of NVIDIA accelerated computing and AI technologies. Integrate NVIDIA frameworks, libraries, GPUs, CPUs, networking, and software into scientific workloads at supercomputing scale. Lead research collaborations, trainings, workshops, lectures, and demonstrations; mentor researchers; track emerging trends; develop prototypes; and provide feedback to NVIDIA Engineering. Support publications, conference presentations, and technical content while serving as a trusted technical advisor.

Develop motion planning, decision-making, vehicle control, and estimation algorithms for autonomous vehicles. Implement mission-critical real-time C++ for embedded automotive systems, build simulation and analysis tools in Python and C++, integrate with perception and platform teams, validate software on vehicles, define safety and performance metrics, analyze field data, and implement safety mitigations.

Lead Essity’s AI technical architecture strategy and roadmap, translating business goals into scalable end-to-end AI solutions. Partner with business leaders, data scientists, AI engineers, and technology providers to prioritize and pilot use cases. Evaluate AI technologies, conduct data/model/software audits, ensure compliance with AI risk standards, and support model recalibration and retraining.

Designs and develops large-scale SAP software solutions for financial consolidation, planning, forecasting, reporting, and performance management. Maintains ABAP code and builds SAP HANA, BPC, SAC, Fiori, and PaPM components. Integrates Google Cloud, AI/ML, and Python models with SAP platforms. Collaborates with architects, engineers, product owners, and finance stakeholders while ensuring reliability, testing, compliance, audit readiness, and regulatory alignment across the software lifecycle.

Conduct advanced research in artificial intelligence and machine learning, including deep learning, graphical models, reinforcement learning, computer perception, natural language processing, and data representation. Define complex business problems, design and deliver modeling solutions, evaluate model performance, establish scientific and engineering specifications, and build analytical roadmaps. Assess production implementation requirements, improve data capture methods, apply statistical and mathematical techniques, and resolve root causes and process bottlenecks.

Lead the Production Inference team of research scientists and ML engineers. Own people development, technical direction, research and development roadmaps, architecture decisions, and model-serving reliability, efficiency, latency, and cost performance. Partner with research, infrastructure, product, and commercial stakeholders; guide production deployment and lifecycle improvements; and recruit technical talent. The role emphasizes leadership and technical reviews rather than hands-on coding.

Design, build, deploy, and operate production-grade machine learning systems for retail media, including sponsored product ranking, audience segmentation, campaign optimization, attribution, and performance measurement. Develop end-to-end ML pipelines, ensure model reliability and observability, continuously improve performance, and communicate technical decisions to product, engineering, and business stakeholders.

Design, develop, deploy, and operate production-grade machine learning systems for retail media, including sponsored product ranking, audience segmentation, campaign optimization, attribution, and performance measurement. Build scalable ML pipelines, monitor model performance, ensure reliability, and communicate technical decisions to product, engineering, and commercial stakeholders. Contribute to engineering standards and knowledge sharing.

Design, build, test, and improve plugin-based forecasting models from business need through production deployment. Own ML and modeling initiatives end to end, evaluate performance across customer environments, distinguish generalizable solutions from customer-specific requirements, and use AI-assisted engineering tools. Work autonomously with customers and cross-functional stakeholders in a distributed international team, with occasional travel.

Build and maintain Ergodic AI’s AI platform across back-end and front-end systems. The role involves developing with Python web frameworks and JavaScript/TypeScript, integrating with client technology stacks and workflows, applying AI, ML, and LLM concepts, and contributing to DevOps, cloud deployment, testing, and infrastructure practices. As an early-stage hire, the engineer will help shape the product and solve complex data and AI challenges.

Owns an AI-native fintech product vertical end-to-end, including strategy, roadmap, technical design, delivery, metrics, and launch. The role covers APIs, data flows, ledgering, reconciliation, security, scalability, regulatory requirements, financial rails, AI evaluation, safeguards, and cross-functional alignment across engineering, compliance, operations, treasury, finance, and design.

Lead data science efforts: explore, clean, analyze structured and unstructured data; develop predictive models, NLP/text-mining solutions, visualizations, and algorithms; guide teammates and advise clients on data-driven decisions. Work may support government and defense customers requiring security clearance.

Designs, develops, deploys, operationalizes, and maintains enterprise-scale data pipelines, workflows, and analytic applications. The role organizes disparate structured and unstructured data for reporting, analytics, and applied production AI. Responsibilities include assessing, designing, building, and maintaining solutions while collaborating with analysts, developers, data engineers, and data consumers in an agile environment. The engineer will also guide multidisciplinary teams and may support mission-driven defense projects.

Leads international commercial excellence strategy across DePuy Synthes markets. Owns sales force effectiveness, commercial analytics, business intelligence, CRM strategy and governance, data quality, incentive planning, performance reporting, and digital enablement. Partners with regional leaders to improve sales productivity, resource allocation, forecasting, and customer engagement. Manages distributed teams, vendors, governance frameworks, change initiatives, talent development, and multi-year capability roadmaps while deploying AI/ML-enabled solutions and standardizing commercial processes globally.

Lead neuroscience R&D for EEG-based BCI: develop signal-processing and classification algorithms, design/execute human-subject experiments, integrate neural data with hardware/software, validate and ensure regulatory and ethical compliance, and mentor junior researchers.