Top Machine Learning Jobs in Germany

Leads Tide’s engineering organization for fraud, financial crime, and ongoing monitoring platforms. Owns engineering strategy, decisioning infrastructure, model lifecycle, agentic AI deployment, and global platform scalability. Partners with risk, compliance, operations, product, and data science leaders to improve fraud detection, reduce losses and monitoring costs, automate workflows, and meet regulatory requirements across multiple markets.

Lead data strategy, architecture, governance, quality, compliance, and technology adoption. Translate stakeholder needs into scalable data initiatives, support advanced analytics and AI/ML, promote data literacy, and guide cross-functional teams toward data-driven decision-making.

Build quantum sensing and magnetometry capabilities using NV centres, optically pumped magnetometry, modelling, experimentation, and machine learning. Characterise sensing systems, develop digital twins, improve calibration, investigate biomagnetic and industrial applications, support patents and commercialisation, publish research, pursue grants, collaborate with faculty, and supervise student projects. The role combines hands-on experimental physics with modelling and applied outcomes.

Develop and operate algorithmic trading solutions for European intraday power markets. Responsibilities include market analysis, modeling, backtesting, coding, testing, deployment, monitoring, and performance improvement. The role supports renewable portfolio balancing, platform reliability, and market expansion in Spain, France, and Italy. It involves collaboration with traders and market specialists, plus daytime standby duties on weekends or holidays when needed.

Drive enterprise sales growth for IQVIA’s AI-powered pharmacovigilance and drug safety technology across EMEA. Responsibilities include prospecting, developing strategic accounts, managing the full sales cycle, exceeding quotas, engaging senior safety stakeholders, and collaborating with product, consulting, hosting, and managed services teams. The role requires experience selling complex SaaS, technology, consulting, and managed services solutions to pharmaceutical, biotech, medical device, and clinical research organizations, with strong knowledge of drug safety and pharmacovigilance.

Develop streaming technology for Windows virtual desktop infrastructure in mixed reality environments. Design, implement, optimize, debug, and profile C++ software across graphics, networking, video, audio, and device integration. Improve streaming quality, responsiveness, reliability, observability, and performance across Windows and Android hardware. Collaborate with stakeholders, create technical designs, guide engineers, manage on-call responsibilities, and resolve production issues.

Leads a strategically important Lounge by Zalando customer or business mission across Product, Engineering, Design, Analytics, and Applied Science. Owns multi-year strategy, measurable outcomes, prioritization, technical and data direction, cross-functional execution, experimentation, and continuous improvement. Builds and coaches high-performing teams, contributes to the technology leadership team, aligns with group organizations, and drives scalable capabilities, innovation, and competitive advantage through evidence-based decision-making and emerging technologies.

Develop and deploy spatial perception models for ADAS/AD, including BEV and occupancy-based architectures. Lead large-scale distributed training, synthetic data validation, model quantization, compression, and edge optimization for automotive SoCs. Translate research into production pipelines, benchmark accuracy and performance, conduct experiments, and build regression testing. Collaborate with research and engineering teams while mentoring junior engineers and maintaining high standards for code quality and documentation.

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.

Develop AI-augmented blockchain risk and threat intelligence systems, including autonomous monitoring and investigation workflows. Lead forensic investigations into crypto theft, fraud, and market manipulation. Research post-quantum cryptography and quantum threats to blockchain security, evaluate migration paths, and collaborate with internal teams, external stakeholders, and academic institutions to deploy emerging security tools.

Lead system-level architecture for a first-of-a-kind stellarator power plant, integrate plasma, magnets, cryogenics, and controls; close design loops with subsystem teams, quantify model uncertainties, run first-principles and reduced-order studies, and turn analyses into actionable engineering decisions to optimize performance, margin, and cost.

Lead the vision, strategy, and execution of company-wide data and machine learning products. Manage a senior cross-functional team, guide projects from business problem through production deployment, analyze large datasets, build data pipelines, establish evaluation and monitoring practices, and develop ML infrastructure. The role includes production LLM and agentic AI work, stakeholder collaboration, recruiting, and team development.

Lead Prior Labs’ SAP partnership and go-to-market motion for TabPFN, enabling SAP sellers, shaping co-sell and commercial frameworks, managing lighthouse accounts, developing industry use cases, and extending partnerships across hyperscalers, marketplaces, and systems integrators. Own joint business and pipeline plans, reporting, and build a specialist partnerships team while working with data science and ML buyers.

Develops thermodynamics-based and AI/ML-enabled predictive models for pharmaceutical formulation and process development. The role analyzes physicochemical data related to solubility, phase behavior, crystallization, stability, and material interactions; builds hybrid mechanistic and machine-learning tools; validates models; assesses uncertainty; and translates complex data into formulation, risk-assessment, and experimentation insights. The scientist collaborates with modeling experts and laboratory teams and communicates findings to technical and business stakeholders.

Develops thermodynamics-based and AI/ML-enabled models for pharmaceutical formulation and process development. Responsibilities include predicting solubility, phase behavior, crystallization, stability, material compatibility, and process performance; integrating mechanistic and experimental data; validating models; assessing uncertainty; creating decision-support tools; and communicating actionable insights to multidisciplinary stakeholders. Requires a PhD-level background and strong expertise in thermodynamics, quantitative modeling, physicochemical data analysis, and scientifically interpretable AI/ML methods.

Own customer AI onboarding from initial execution through go-live and continuous improvement. Validate camera and input data quality, identify edge cases, maintain datasets and SOPs, track success metrics, communicate blockers, and coordinate installation teams to ensure reliable, consistent deployments. Improve onboarding workflows through documentation, checklists, templates, and tool enhancement recommendations. The role requires structured execution, strong communication, process discipline, technical systems comfort, and preferably manufacturing or process experience.

Lead R&D for industrial robotic manipulators, including modeling, planning, control, perception, machine learning, simulation, and hardware integration. Develop and test robotic prototypes, planning algorithms, middleware, software architectures, pose estimation, segmentation, and autonomous grasping systems. Deploy and validate solutions using ROS-compatible hardware, sensors, robot arms, and real-world environments.

Own customer onboarding from initial execution through post-launch iteration. Validate camera and input data quality, identify edge cases, maintain datasets, document process variance, track success metrics, and communicate progress and blockers. Improve onboarding workflows through checklists, documentation, templates, and tool feedback. Coordinate with installation teams to ensure camera setups support reliable, consistent AI onboarding across stations.

Supports Account Executives throughout the sales cycle by leading technical discovery, solution design, demonstrations, workshops, proofs of concept, evaluations, and technical validation. Translates engineering, simulation, HPC, AI, and infrastructure requirements into Rescale recommendations, documents opportunities in Salesforce, resolves technical risks, supports negotiations, and ensures effective post-sale handoffs across Northern Europe.

Manage full-cycle technical recruiting for AI, machine learning, and AI safety teams. Responsibilities include sourcing niche and passive talent, market mapping, talent-pool development, candidate engagement, stakeholder collaboration, offer negotiation, candidate experience, and recruitment-process improvement. The role requires strong knowledge of AI research recruiting, bilingual German and English communication, and the ability to operate effectively in a fast-paced startup environment.

Design, build, operate, and scale software platforms supporting the machine learning lifecycle. Responsibilities include developing ML pipelines, deploying and optimizing models for cloud and edge environments, managing secure data platforms, building REST APIs and internal tools, implementing testing and CI/CD, and maintaining production ML tooling. The role also involves architecture, automation, stakeholder management, requirements engineering, and technical decision-making.

Lead a pod of data scientists (25%) while spending most time (75%) developing, validating, and deploying ML algorithms from sensor and imaging data for clinical decision support. Drive technical standards, production-quality code, cross-functional validation with engineers and clinicians, and contribute to Data Science leadership and regulatory readiness.

Lead biomarker and mechanism-of-action research supporting clinical translation. Develop computational pipelines, analyze complex biological datasets, interpret findings, and present actionable insights to cross-functional teams. Mentor junior scientists, lead project activities, uphold data integrity and reproducibility, and contribute to scientific publications and reports. The role requires expertise in bioimaging or single-cell sequencing analysis, statistical analysis, and Python or R, with machine learning and automated pipeline experience preferred.

Provides proactive executive support to the CEO through agenda and travel management, time and priority optimization, stakeholder communication, project coordination, logistics, and problem-solving. The role involves frequent international travel, varying time-zone hours, confidential work, and ad hoc tasks. Candidates should be organized, adaptable, tech-savvy, communicative, fluent in English and German, authorized to work in Germany, and able to travel internationally on short notice.

Designs, develops, operationalizes, and maintains enterprise-scale data applications and scalable ETL/ELT pipelines. Processes structured and unstructured data, creates reporting and analytics solutions, and develops data visualizations using tools such as Tableau, Qlik, Power BI, or Foundry. Collaborates with multidisciplinary teams in agile environments and supports mission-driven defense and intelligence projects.