Top Machine Learning Jobs in Munich

Guide customers through Zscaler’s Zero Trust adoption as a post-sales technical contact. Build stakeholder relationships, provide technical guidance and best practices, develop integration strategies, coordinate complex escalations, identify adoption risks, and collaborate on mitigation plans. The role also contributes to customer success playbooks and best-practice resources while advising on cloud, networking, security, and AI-powered solutions.

Develops and integrates radiating components and passive radiation-pattern structures for multiband base-station antennas. Responsibilities include 3D and 2D electromagnetic simulation, prototype RF measurements, performance optimization, troubleshooting, technical documentation, and supporting the product lifecycle through mass production. The role collaborates with international cross-functional teams and requires relocation to Rosenheim, Germany.

Leads strategic Professional Services sales and advisory activities across the DACH region. Positions Workday’s AI, extensibility, analytics, and transformation capabilities; conducts consultative discovery; aligns Global Systems Integrator partners; negotiates services agreements and statements of work; manages forecasts; and builds executive customer relationships. Requires enterprise software or digital transformation consulting experience, change management expertise, complex sales success, German and English fluency, and travel up to 35%.

Defines success metrics and evaluation strategies for ML products, including simulations, benchmarks, guardrails, and structural consistency checks. Partners with Product Owners and Data Science teams to translate business questions into analytical problems and model results into business decisions. Builds rapid prototypes, offline evaluations, self-service analytics, and AI-assisted tools while establishing evaluation standards across product teams.

Six-month machine learning internship focused on training, evaluating, and deploying deep learning models for satellite imagery and deforestation detection. Responsibilities include implementing computer vision and remote sensing research, improving model robustness and explainability, scaling geospatial pipelines, and owning projects from data preparation through deployment. The role requires strong PyTorch and Python skills, research implementation ability, software engineering practices, and effective communication.

Designs and maintains enterprise integrations across SaaS platforms, cloud infrastructure, data systems, and internal applications. Builds GitLab CI/CD pipelines, Terraform-based AWS infrastructure, automation workflows, APIs, event-driven data pipelines, and AI-enabled middleware using Node.js or Python. Manages MCP servers, integrates machine learning and LLM services, troubleshoots system performance, and ensures secure, reliable, well-documented solutions through collaboration, testing, and continuous improvement.

Own the vision, strategy, and roadmap for airborne perception and sensor-fusion software on uncrewed combat aircraft. Translate operational needs into requirements, KPIs, acceptance criteria, and prioritized releases. Partner with AI, perception, autonomy, navigation, systems, safety, and flight-test teams to manage technical trade-offs and validate capabilities through simulation and flight testing. Engage customers, military stakeholders, and partners while shaping data strategy, collaborative fusion, navigation, and common operating picture capabilities.

Serves as a cross-organizational technical authority, translating technology strategy into architectures, experiments, advanced-technology initiatives, and product capabilities. Leads emerging technology programs from research through commercialization, builds specialized technical teams, advises executives on technology decisions, and connects HARMAN engineering, research, business, Samsung, academic, and external partner communities. The role requires broad expertise across software, hardware, AI/ML, embedded systems, sensing, connectivity, audio, and physical systems, alongside strong commercial judgment and communication skills.

Leads the Data Tribe, establishing data governance and management standards, ensuring engineering compliance, and identifying data-driven business opportunities. Oversees data infrastructure and analytics, advises teams on data-driven practices, mentors Team Leads, manages stakeholders and projects, and serves as Data Protection Coordinator for Engineering.

Dryft is accepting open applications for candidates interested in building AI models that automate complex decisions in manufacturing operations. The company captures operator expertise, simulates decision outcomes, and supports supply chain, production planning, engineering, and industrial operations. It seeks humble, hardworking, fast-learning, kind, customer-focused people willing to take ownership and solve difficult problems.

Lead research on interactive avatar models and real-time generative AI video agents. Set research direction, advance multimodal perception and reaction generation, post-train diffusion models, build evaluation frameworks, define datasets, and guide research-to-production efforts. Mentor researchers and influence technical decisions across research, data, and engineering teams.

Build and deploy perception systems for autonomous platforms, including object detection, tracking, semantic segmentation, and depth estimation. Prepare datasets, train and evaluate models, optimize real-time onboard deployments, extend replay tooling, analyze mission logs, debug field failures, and write production-quality code. The role involves testing systems on recorded mission data and real-world field trials while collaborating with perception, autonomy, and research teams.

As a Research Engineer, you'll develop and manage data systems for text-to-speech projects and enhance machine learning models using innovative strategies.

Leads Germany’s content and omnichannel capabilities for personalized pharmaceutical marketing. Translates local business priorities into technology use cases, governs local adaptations of global capabilities, partners with IT and brand teams, and drives content production, channel enablement, personalization, campaign measurement, AI adoption, and technology roadmaps. Serves as an expert in personalization strategy, content operations, analytics, and emerging commercial technologies.

Lead the team responsible for the architecture, design, and integration of facility-wide monitoring and control systems for a commercial stellarator fusion plant. Own supervisory control software, telemetry, live monitoring, facility data infrastructure, functional safety strategy, physical infrastructure integration, control hardware R&D, and subsystem interface standards. Build high-performing teams and translate complex, safety-critical R&D into reliable operational systems.

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.

Owns Germany’s content and omnichannel marketing capabilities for pharmaceutical commercial applications. Translates local business priorities into technology use cases, governs global capability adaptations, partners with IT on technology roadmaps, and enables content production, channel activation, personalization, and campaign measurement. Serves as a subject matter expert on emerging AI and marketing technologies while supporting cross-functional decision-making, documentation, and efficient execution.

Leads the design, development, deployment, and evaluation of machine learning, forecasting, recommendation, and analytical solutions. Partners with Product, Commercial, Engineering, and Data teams to solve business problems, define metrics, build scalable pipelines, and deliver measurable impact. Provides technical leadership and mentorship, promotes model development and governance best practices, and contributes to the data science roadmap.

Build Solidgate’s ML/AI function from the ground up, developing real-time payment routing models and production pipelines. Own the full ML lifecycle from experimentation and A/B testing through deployment, while solving modeling challenges involving large-scale transactional data. Partner with Product, Engineering, and Data Platform teams to deliver measurable improvements in conversion, approval rates, losses, and revenue.

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.

Develops new business for AI-driven software solutions by identifying prospects, managing the full sales cycle, preparing proposals and tenders, negotiating contracts, and transitioning new accounts to delivery teams. The role builds customer relationships, maintains CRM records, supports revenue growth, attends relevant industry events, and expands professional networks. It requires IT sales experience, AI project expertise, knowledge of software development lifecycles, advanced English and German, and strong negotiation and communication skills.

Lead and grow the Money & Risk engineering team responsible for fraud prevention, risk scoring, reconciliation, settlement, and chargebacks. Own technical direction for scalable, auditable, secure payment systems across 80+ countries. Drive architecture, engineering standards, AI-assisted development, hiring, coaching, and cross-functional delivery with Product, Data, Finance, Compliance, and Operations.

Leads AI transformation across automotive operations by redesigning end-to-end processes, defining data and AI requirements, coordinating cross-functional delivery, and driving adoption and value realization. The role focuses on embedding AI into operational decision-making across costing, risk management, supply chain visibility, manufacturing, and other value streams. It bridges business stakeholders with data, architecture, IT, and AI teams while establishing roadmaps, governance, KPIs, enablement materials, and measurable business outcomes.

The AI Engineer will build data pipelines and improve ML systems for reliability in production. Responsibilities include schema design, data infrastructure, and model evaluation, ensuring high-quality outputs and integration with product workflows.

Own the Mapping & Content product domain end to end, including strategy, prioritization, economics, and outcomes. Lead efforts to match hotel rooms and content across suppliers, languages, and formats with high accuracy and coverage. Partner closely with engineering and data science teams on entity resolution, search, matching, catalog, identity, recommendation, and content-quality problems. Identify high-value failures, make trade-offs between precision and coverage, and help build Nuitee’s product organization in a fast-moving environment.