Top Machine Learning Jobs in Munich

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 complex enterprise customer engagements as the senior technical authority for data and AI strategy. Drive Databricks adoption, consumption, competitive displacement, and revenue growth through architecture, migrations, streaming systems, lakehouse platforms, and AI/ML solutions. Manage executive relationships, orchestrate cross-functional teams, mentor solutions architects, develop competitive strategies, and contribute to technical thought leadership. Weekly travel is required.

Lead end-to-end architecture, implementation, and delivery of Blue Yonder Warehouse Management and related execution solutions. Serve as the primary client contact, manage timelines, budgets, risks, and deliverables, and lead solution teams and integrations. Provide functional and technical guidance, mentor junior staff, align solutions with business objectives, and collaborate with project managers, delivery partners, and stakeholders to deliver successful client outcomes.

Lead GTM operations across EMEA and APAC by developing commercial growth strategies, forecasting frameworks, territory plans, sales methodologies, dashboards, and pipeline management processes. Partner with executive leaders across Sales, Finance, Marketing, Customer Success, and Partnerships. Use Salesforce, Outreach, Snowflake, AI, and machine learning to improve forecast accuracy, pipeline conversion, reporting automation, and sales productivity.

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.

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.

Manage relationships with AI-native startups, scaleups, and labs in Germany. Understand customer goals, develop AI solution strategies, coordinate NVIDIA technical and business resources, drive adoption of AI platforms, build ecosystem partnerships, develop customer references, identify emerging use cases, and represent NVIDIA at industry events. The role requires deep AI industry knowledge, strategic planning, cross-functional collaboration, and familiarity with NVIDIA’s software, server, and cloud stack.

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.

As a Senior Forward Deployed Engineer, you'll deliver AI solutions, engage with customers, and lead project lifecycles, including deployment and integration.

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

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.

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 end-to-end enterprise sales in Financial Services for Cloudflight’s tech portfolio. Generate pipeline, engage executives, develop tailored solutions and proposals, close complex deals, and grow strategic accounts. Coordinate with delivery, architects, and partners (Microsoft, Databricks, AWS). Manage CRM, forecasting, and cross-sell/upsell activities across cloud, data, AI/ML, and custom software offerings.

Design and develop control architectures and advanced control algorithms for integrated electrical and automation systems. Lead subsystem integration for synchronized plant operation, modernize power management strategies, and implement diagnostics and predictive maintenance to improve reliability and performance.

The Account Executive will leverage technical expertise in enterprise SaaS sales to drive revenue growth, build partnerships, and represent Neural Concept's technology in engineering sectors.

Develop and integrate reinforcement learning agents into autonomous aerial systems, ensuring reliability and performance. Collaborate with teams and enhance the software stack while mentoring peers.

As Lead Systems Engineer, oversee integration of EO/IR sensing systems, manage technical suppliers, define requirements and ensure operational readiness.

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.

Develop and optimize machine learning and computer vision models for pose estimation, 3D reconstruction, object detection, segmentation, and volumetric modeling. Build Python-based training and data pipelines, process point clouds and meshes, prototype geometry-based algorithms, support data collection, and integrate algorithms into Dockerized CI/CD workflows. Collaborate with R&D, cloud, and data operations teams while documenting experiments and technical decisions.

Lead the end-to-end search experience: improve relevance, discovery, ranking, and UX across platforms. Collaborate with data science/ML to define metrics and experiments, prioritize a roadmap, and optimize search infrastructure, autocomplete, filters, and zero-results handling for complex health-related journeys.

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.

Design AI-powered healthcare product experiences for clinical workflows, including documentation, patient summaries, search, agent workflows, multimodal interactions, uncertainty handling, and approval flows. Lead discovery, prototyping, and user validation; collaborate with ML engineers, product managers, software engineers, and clinicians. Contribute AI interaction patterns and components to the design system, establish AI design principles, and promote trustworthy, high-quality experiences for hospital users.

Design, develop, and maintain high-performance, secure Java backend services and APIs. Ensure reliability, scalability, and cost-efficiency across microservices, databases, messaging systems, and capacity planning. Troubleshoot, profile, benchmark, and optimize systems (including ML applications) and collaborate with Kazakhstan stakeholders.

Lead technical discovery, solution design, demonstrations, and proof-of-concept support for Anaconda’s AI and data science platform across EMEA. Partner with account executives on complex deals, create reusable technical content, represent customer needs to product and engineering, and coordinate with cross-functional teams through implementation handoff. Manage multiple opportunities independently while improving technical win rates, deal expansion, sales velocity, and regional pipeline development.

Deliver operations-focused strategy consulting engagements across procurement, supply chain, manufacturing, and digital operations. Lead workstreams, perform advanced analytics and ML-driven solutions, synthesize recommendations, manage client relationships, and coach junior team members to drive sustainable performance improvements.