Top Machine Learning Jobs in Munich

The Applied Machine Learning Scientist will innovate and implement ML algorithms to enhance advertising performance, collaborate with engineers, and prototype in data-driven models.

The role involves enhancing operational effectiveness in military operations through exercise development, collaboration, and innovation methodologies, focusing on integrating advanced technologies.

The Sales Account Manager will develop business from new accounts, manage strategic partnerships, collaborate with leadership, and enhance BioCatch's brand in Germany while exceeding sales objectives.

Ship AI product features combining engineering and ML; build and improve agent workflows; optimize latency, cost, and reliability; track AI research and turn it into product; build self-improving loops that run experiments and learn from feedback.

Design, build, and maintain production-grade GenAI systems and Python-based APIs. Implement end-to-end RAG, vector DBs, multi-agent systems, and secure MCP infrastructure. Optimize LLM integrations (OpenAI, Anthropic), event-driven architectures, and real-time messaging. Collaborate cross-functionally, create and refine prompts, and ensure reliability, scalability, and security in production generative AI solutions.

Design and develop image/video diffusion models, perform large-scale model training, maintain data for training, and optimize models for production use.

As an ML Application Engineer, you'll analyze engineering data, develop ML solutions, and train customer teams for AI adoption, working closely with engineering clients to enhance product design workflows using advanced technologies.

Lead a team of ML Engineers to develop and optimize ML systems, ensuring high-quality clinical care through AI. Foster collaboration across teams for innovative AI/ML features.

The Senior Technical Product Manager will shape product strategy for Constructor's platform, ensuring capabilities support scalability and security for learning applications.

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 pre-sales engagements to design and present AI-driven customer experience solutions using Genesys Cloud. Conduct discovery workshops, build demos and business cases, translate technical concepts to business value, collaborate with account teams and partners, and support adoption of conversational AI, automation, and cloud integrations across DACH.

Serve as the single point of contact for mid-to-enterprise customers, guiding onboarding, deployment, configuration, and adoption of Sophos cybersecurity solutions. Drive customer success through proactive account health monitoring, QBRs, technical guidance, risk mitigation, cross-functional collaboration, and stakeholder enablement to maximize value realization and secure renewals.

The Applied AI Engineer drives product adoption, manages customer relations, and collaborates on state-of-the-art GenAI applications, ensuring successful deployment across industries.

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.

Lead product vision and discovery for a genomics-driven diagnostic and personalization platform. Validate hypotheses with patients, clinicians, and partners; translate research into product specs; coordinate labs and data providers; partner with engineers and researchers to build AI prototypes; shape data, regulatory, and GTM strategy while making core product and architectural decisions.

Build core components of a diagnostic and personalization platform: backend data pipelines, frontends, services for genomic data ingestion, ML model integration, APIs, and cloud infrastructure. Collaborate with product and ML teams, iterate on prototypes and MVPs, and make architectural decisions supporting scalability and reliability.

Build backend services and data infrastructure for a geospatial intelligence platform, focusing on scalable design and data architecture for large datasets.

Dragonfly is seeking Software Engineers for various portfolio companies, focusing on crypto technologies. Engineers of all experience levels are needed across multiple stacks.

Create and review realistic, locale-specific robotics and natural sciences tasks in the target language, apply scoring rubrics, evaluate AI and human responses for accuracy and regulatory alignment, and produce high-quality gold-standard solutions and feedback.

As an ML Solution Consultant, you'll guide R&D teams in using ML tools, ensuring effective data structuring, and maximizing the value of scientific data.

As a Machine Learning Engineer, you'll integrate intelligent systems into healthcare, build and deploy ML models on clinical datasets, and work with federated learning frameworks.

As an Engagement Manager, you'll ensure customer success in protein R&D by building relationships, tracking metrics, and leading cross-functional teams. You'll manage enterprise accounts and advocate for customers while aligning their needs with Cradle's offerings.

The role involves improving biometric identification and anti-spoofing models, leading research initiatives, and collaborating across teams in a production environment.

Develop and evaluate AI/ML compiler technology for edge applications. Adapt and extend MLIR/IREE compilation flows, integrate custom NPUs, align solutions with business line requirements, and collaborate with partners to integrate compiler frameworks into NXP's AI tooling while tracking state-of-the-art advances.

Lead and scale machine learning engineering teams, develop standards, drive technical strategy, and enhance collaboration across functional teams.