Top Machine Learning Jobs in Munich

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 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.

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.

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.

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 NVIDIA’s developer relations strategy across EMEA Smart Spaces and Local Government ISV ecosystems. Build partner relationships, deliver technical enablement, support integrations, guide startups, and drive adoption of NVIDIA AI and computing platforms. Collaborate with sales, solution architecture, engineering, product, and marketing teams; translate partner needs into product feedback; demonstrate AI solutions; and influence technical and commercial growth. The role requires deep AI/ML and generative AI expertise, technical collaboration skills, and experience scaling developer programs.

Designs, develops, and deploys production-grade machine learning systems focused on LLMs, Generative AI, and deep learning. Responsibilities include building scalable ML libraries and research workflows, optimizing distributed training and inference, improving experiment tracking and model lifecycle management, and bridging research prototypes with robust implementations. The role requires collaboration with data science and platform teams, strong software engineering practices, cloud and MLOps expertise, and mentoring across the technical team. Biomedical, clinical, or omics data experience is preferred.

Review and annotate images by identifying people, actions, and predefined categories. Follow detailed annotation guidelines, maintain accuracy and consistency, review completed work, and help create high-quality datasets for AI models. The role requires strong attention to detail, independent work, reliability, and EU citizenship with residence in the European Union.

Develop, validate, deploy, and maintain machine learning solutions for medical device manufacturing and CAD/CAM systems. Build deep learning and multimodal AI models using computer vision, 3D geometry, meshes, images, and structured data. Integrate models into production systems, conduct performance analysis, maintain ML workflows, and translate research into practical manufacturing applications while collaborating with engineering, manufacturing, and product teams.

Develop and maintain high-load, real-time personalization services for global e-commerce platforms. Improve shopper experiences and business KPIs through applied machine learning, user interaction modeling, personalization and recommender systems, hypothesis validation, and A/B testing. Collaborate with engineering teams and business stakeholders to research, deliver, and communicate personalization capabilities and outcomes.

Leads consultative discovery, technical qualification, solution design, executive presentations, and sales campaigns for AspenTech industrial software. Partners with sales teams to align technology with measurable customer value, develops industry-specific messaging, engages senior executives, provides product feedback, coaches sales personnel, and represents the company at industry events. Requires extensive industrial software or solution consulting experience, technical domain expertise, multilingual fluency, and European work authorization.

Build and grow Cloudera’s sovereign cloud business across EMEA. Develop relationships with sovereign cloud providers and enterprise customers, create marketplace offerings, drive partner enablement and sales motions, generate pipeline, and manage regional forecasts and bookings. The role requires expertise in enterprise cloud, data, AI/ML, sovereignty regulations, complex multi-stakeholder deals, executive communication, and cross-functional collaboration.

AI/ML Engineers will build and deploy AI-native products, autonomous agents, LLM applications, RAG systems, and production ML pipelines. Responsibilities may include integrating AI into crypto infrastructure and consumer products, fine-tuning and evaluating models, optimizing inference, and developing agentic workflows and machine-to-machine payment systems. Engineers will work end-to-end with high-ownership teams in fast-moving environments.

Own enterprise customer relationships from kickoff through adoption and ongoing value realization. Lead success plans, QBRs, executive conversations, escalations, stakeholder alignment, training, and strategic recommendations. Translate technical capabilities and performance data into business outcomes such as revenue, conversion, and customer experience. Partner with Account Management to support retention and expansion while improving scalable onboarding and support processes.

Drive business development and close high-value enterprise deals with global biotech and biopharma accounts across Europe. Own strategic customer relationships, deliver recurring revenue, partner with technical and customer success teams on complex proposals, provide market insights for product direction, build industry credibility, and improve enterprise sales processes and playbooks.

Leads NVIDIA’s developer relations strategy for manufacturing and industrial ecosystems across EMEA. Advises developers, software vendors, startups, OEMs, and integrators on AI and accelerated-computing solutions, including robotics, digital twins, simulation, computer vision, and predictive maintenance. Creates technical enablement assets, supports onboarding and integration, analyzes ecosystem opportunities, gathers developer feedback, and collaborates with engineering, product, marketing, sales, and partners to drive adoption and production-ready implementations.

Conduct advanced research in artificial intelligence and machine learning, including deep learning, graphical models, reinforcement learning, computer perception, natural language processing, and data representation. Define complex business problems, design and deliver modeling solutions, evaluate model performance, establish scientific and engineering specifications, and build analytical roadmaps. Assess production implementation requirements, improve data capture methods, apply statistical and mathematical techniques, and resolve root causes and process bottlenecks.

Own the full machine learning lifecycle, from exploration and prototyping through production deployment and operations. Build ML models, training and evaluation pipelines, experiment tracking, model monitoring, and drift detection using Python, MLflow, AWS, and SQL. Collaborate with data engineering, contribute to reliable data pipelines, maintain high engineering standards, and mentor engineers and data scientists. Recommender systems, AdTech, deep learning, GCP, and Snowflake experience are advantageous.

Conduct research across the full machine learning lifecycle, including ideation, model design, implementation, evaluation, training, inference optimization, and deployment. Develop novel machine learning methods and foundation models, establish evaluation protocols, scale training with GPUs or TPUs, and improve research engineering infrastructure for rapid experimentation.

Develops new business and revenue across DACH banking and financial-services accounts. Owns strategic account plans, complex enterprise sales, pipeline forecasting, deal closure, customer and partner relationships, and executive-level engagement. Collaborates with business development, sales engineering, account management, and leadership teams to drive adoption, customer success, and revenue growth. Represents the company at relevant events and supports go-to-market initiatives. Frequent domestic and infrequent international travel is required.

Own the DACH market launch for Nebuly, generating pipeline through an established enterprise network and managing the full B2B SaaS sales cycle. Target mid-market and enterprise accounts with €100K+ ACV potential, navigate complex stakeholder groups, build business cases, negotiate, and close deals. Represent Nebuly at market events, collaborate with sales engineering and partners, and develop system integrator and advisory relationships. The role requires German and English fluency, strong enterprise relationships, technical sales ability, and experience closing large contracts without inbound or SDR support.

Develop and demonstrate Physical AI solutions on NVIDIA and hyperscaler platforms. Advise customers and partners, optimize GPU-accelerated training and inference pipelines, conduct proof-of-concepts, and collaborate with Engineering, Product, Sales, and Marketing teams. Build technical relationships, gather customer feedback, support enterprise architecture integration, and evangelize accelerated computing and generative AI to developers, researchers, executives, and technical leaders.

Provides strategic and hands-on biostatistical leadership across pharmaceutical discovery, translational, biomarker, and early research programs. Designs studies, analyzes complex biological datasets, develops advanced statistical methods and reproducible R workflows, and translates evidence into portfolio decisions. The role collaborates with quantitative and scientific functions, supports publications and external partnerships, mentors statisticians, and advances data-driven analytical practices.

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.