Top Machine Learning Jobs in Munich

Leads analytical methodology and evaluation for AI-based healthcare and pharmaceutical workflows. Owns model selection, cohort and HCP segmentation, agent decision logic, and evaluation frameworks. Partners with engineering, data architecture, and governance teams to productionize rigorous analytical methods, identify new data and techniques, communicate insights, and mentor data science and engineering colleagues.

Leads ad hoc and exploratory analyses for medical and business questions across a global Medical Insights organization. Prepares and validates datasets, translates ambiguous stakeholder needs into decision-ready findings, and maintains analytical documentation. Tests new data sources, methods, and AI-enabled approaches through proof-of-concept analyses to guide platform investments and roadmap decisions. Partners with business and product stakeholders while supporting compliant, reproducible use of regulated data.

Leads data science methodology and advanced analytics for AI-enabled Medical Affairs workflows. Develops and evaluates statistical, machine-learning, NLP, and AI models using healthcare and real-world data; defines validation, monitoring, and decision frameworks; partners with engineering, governance, and business teams to operationalize solutions. Provides technical leadership, mentorship, documentation standards, and strategic guidance while ensuring privacy, compliance, responsible AI use, and clear communication of analytical findings.

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.

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.

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.

Develop research methods and systems for matter-specific legal AI, including model and agent adaptation, data curation, benchmark design, training, inference, experimentation, and evaluation infrastructure. Collaborate with founders, engineers, legal experts, and enterprise partners to translate legal workflows into agentic systems and production capabilities. Help shape the company’s technical direction and research culture while owning empirical research and engineering projects end to end.

Design legal AI tasks, datasets, workflows, and evaluation rubrics; assess system outputs for legal accuracy and usefulness; translate legal processes into agentic workflows; lead enterprise pilots and implementations; and support customer discovery, demonstrations, and go-to-market initiatives. The role requires close collaboration with AI researchers and engineers and offers broad ownership in an early-stage company.

Leads the transformation of translational and biomarker data into standardized, AI-ready data products for drug discovery and development. Oversees data standards, catalogs, metadata, harmonization, quality frameworks, APIs, automation, and enterprise integration. Manages a distributed team of 12–15 data stewards and engineers, establishes multi-year strategy, coordinates cross-functional stakeholders, oversees budgets, and advances FAIR data practices, governance, and AI-enabled workflows across therapeutic areas and research partners.

Leads a distributed team transforming translational and biomarker data into standardized, FAIR-compliant, AI-ready data products. Responsibilities include defining data standards, metadata, semantic schemas, quality frameworks, APIs, and integration with enterprise data platforms. The role delivers analysis-ready datasets for precision medicine and biomarker discovery, automates curation and quality assurance, establishes multi-year data roadmaps, coordinates global stakeholders, manages budgets, and advances data governance across labs, studies, therapeutic areas, and partners.

Design, implement, and deploy efficient adaptive machine learning systems that retrain or fine-tune models using production data. The role combines applied research with production engineering, including data strategy, model evaluation, online learning, reinforcement learning, observability, and real-world product development. The engineer will own data products, solve novel technical challenges, and collaborate closely with the founding team on research and product direction.

Develop cloud streaming technology for VDI experiences, focusing on low-latency streaming, graphics, networking, and video codecs. Design, optimize, debug, and maintain C++ software across Windows hardware platforms. Analyze visual quality and responsiveness, collaborate on product requirements and plans, support reliability and observability, and participate in on-call operations while guiding other engineers.

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 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.

Lead the data intelligence dimension of Agileday’s AI product by building AI-ready data foundations, predictive and recommendation capabilities, learning systems, feedback loops, and production data pipelines. Partner with founders and product teams to identify commercially valuable opportunities, shape architecture and quality standards, and move solutions from experimentation into reliable customer-facing products.

Lead the architecture and technical direction of production recommendation systems. Design, develop, deploy, monitor, and continuously improve ML models for candidate generation, ranking, personalization, and product discovery. Translate ambiguous business needs into scalable solutions while balancing quality, latency, reliability, and maintainability. Provide technical leadership through design reviews, mentoring, standards, and cross-functional collaboration.

Own end-to-end hardware development projects from concept through series-production release. Coordinate hardware, software, data science, suppliers, production partners, and Sales Engineering. Manage integration milestones, outsourced work packages, deployments, budgets, risks, quality, and leadership reporting while ensuring customer requirements become delivered systems.

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.

Develop and improve autonomous vehicle planner software that determines driving maneuvers. Monitor software releases, evaluate performance improvements or degradation during daily real-vehicle testing, and participate in test drives. The role requires close collaboration with testing activities and hands-on problem solving in robotics and autonomous driving.

Designs, develops, deploys, and operationalizes AI and machine learning systems for automotive engineering and business operations. The role involves architecting scalable solutions, delivering generative AI and LLM applications, optimizing model performance, implementing MLOps and governance practices, collaborating across technical and business teams, and mentoring junior engineers. The position also requires leading experimentation, validation, system integration, and continuous improvement of production-grade AI solutions.

Designs end-to-end AI transformations for complex enterprise customers. Advises HR, Finance, and IT executives; leads requirements discovery, process design, configuration guidance, data readiness, governance, and adoption workstreams. Partners with Product, Engineering, and technical teams to align AI agents, data models, security, and integrations. The role requires enterprise consulting experience, strong business acumen, AI solution design expertise, executive communication, and travel of up to 50%.

Supports AI and data consulting projects through market sizing, segmentation, pricing, optimization, predictive modeling, KPI development, dashboards, workshops, and executive presentations. The intern analyzes large datasets, develops practical client solutions, communicates complex findings to nontechnical audiences, and contributes to cross-functional strategy teams.

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.

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.