Top Machine Learning Jobs in Munich

Supports Celonis Platform implementations for global customers through process-mining discovery, SQL/Python data transformation, AI and machine-learning solution development, stakeholder workshops, documentation, and quality control. The role helps translate technical findings into business value, improve operational efficiency, and drive customer adoption. It is part of a 12-month graduate program involving collaboration with consultants, product, engineering, analytics, architecture, and support teams.

Supports Celonis Value Engineering for the DACH market by analyzing customer process data, identifying business challenges, translating them into AI and Process Intelligence use cases, quantifying financial impact, and preparing executive presentations. The intern contributes to proof-of-value projects, prototypes machine learning and LLM-based solutions, collaborates with customers and sales teams, and presents data-driven value propositions to decision-makers.

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.

Develop and optimize machine learning models for acoustic detection, sensor fusion, computer vision, and swarm intelligence. Deploy and optimize models on edge hardware using quantization, distillation, and compression. Iterate architectures using field data and benchmarks, while collaborating with hardware and firmware engineers to support efficient deployment on autonomous counter-UAS sensors.

Plans and executes FPV, fixed-wing, and model aircraft flight tests; develops procedures; collects, validates, labels, and annotates test data; builds drone rigs for acoustic characterization; supports field test setup and teardown; and collaborates with data and ML engineers to evaluate autonomous counter-UAS systems. The role includes extensive travel to collect ambient sound data.

Own enterprise customer success for an AI-powered payments intelligence platform. Advise customers on payment performance, authorization rates, cost reduction, and data-driven decisions. Monitor data ingestion and quality, analyze transaction trends and AI-generated anomalies, configure KPIs and dashboards, and support integrations and implementations. Collaborate with Product, Data Engineering, Customer Experience, and Integration teams to translate customer needs into product improvements. Lead business reviews, provide technical guidance, and stay current on payments, analytics, AI, and regulatory developments.

Design, train, and deploy machine learning systems for robotic perception and control. Build data pipelines, MLOps workflows, simulation tooling, synthetic data generation, and models including video, multimodal, world, diffusion, and transformer architectures. Integrate models with physical robotic manipulators and multimodal sensor data, then evaluate and optimize them for reliability, latency, and robustness in real-world factory environments.

Provides technical leadership for AI initiatives, developing Essity’s AI architecture strategy and roadmap. Designs scalable end-to-end AI solutions, translates business needs into technical implementations, evaluates AI technologies, collaborates with data scientists and business leaders, and conducts audits of data, models, and software engineering to support compliance, risk management, and continuous improvement.

Own the greenfield Anti Financial Crime platform, defining its product strategy, roadmap, architecture, and technical requirements. Partner with AML, AFC operations, engineering, and product teams to prevent and detect financial crime, integrate controls into customer journeys, and deliver scalable tooling. Lead milestone prioritization, stakeholder alignment, and end-to-end delivery while balancing execution speed, regulatory diligence, and platform security.

Lead end-to-end deployment, integration, and optimization of ERP, AI, and business application projects. Manage requirements, design, implementation, testing, deployment, and post-launch support. Coordinate engineering, data science, executives, and business stakeholders; oversee integrations, change management, risks, resources, budgets, KPIs, and agile governance. The role requires enterprise software implementation experience and familiarity with AI, automation, analytics, and project management methodologies.

Develop and maintain high-performance Rust and Python simulation and validation frameworks for autonomous air systems. Build Software-in-the-Loop and Hardware-in-the-Loop environments, automated testing, fault injection, regression coverage, and deployment infrastructure. Collaborate with autonomy and systems teams, optimize real-time simulation performance, maintain documentation and benchmarks, review code, mentor colleagues, and improve reliability, safety, and operational performance.

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 the Data Tribe and develops data-driven business value across the company. Responsibilities include establishing data management and governance guidelines, ensuring engineering compliance, advising teams on data-driven practices, mentoring team leads, coordinating data protection for Engineering, and overseeing data infrastructure, analytics, data integrity, and ICT support. The role requires expertise in data science, machine learning, stakeholder management, and data and people project leadership.

Build strategic enterprise relationships in the manufacturing and industrial sectors, identify and develop new business, lead complex sales cycles, and translate client challenges into technology solutions. Advise senior decision-makers on digital transformation involving cloud, software engineering, data, AI/ML, and embedded software. Partner with consulting, engineering, and delivery teams to shape tailored solutions, close complex deals, expand client relationships, and contribute to revenue growth.

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.

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.

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.

Lead SAP’s AI technology strategy and enterprise architecture for AI-native systems. Guide adoption of LLMs, RAG, multi-agent systems, agentic orchestration, evaluation, and responsible AI practices. Align platform and application teams, conduct architecture reviews, set CI/CD and MLOps standards, mentor senior architects, engage executives, and drive secure, high-quality AI adoption across SAP’s product portfolio.

Advise city governments across the Americas on designing, prototyping, and launching digital services. Guide system and data architecture, DevOps, infrastructure, AI and machine learning decisions, rapid prototyping, and end-to-end product delivery. Work hands-on with multidisciplinary teams while coaching clients and influencing technical decisions without direct authority. The role requires senior technical leadership, strong communication, and professional English plus Spanish and/or Portuguese.

Conduct research on 3D generation, reconstruction, and world models. Design, implement, and evaluate state-of-the-art methods and prototypes, collaborate with the research team, present findings, and contribute to publications at leading computer vision, graphics, and machine learning conferences.

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.

Intern will help optimize business processes using digital tools, automation, analytics, AI, and data-driven solutions. Responsibilities include supporting workflow improvements, reducing manual work, manipulating and visualizing data, and exploring machine learning and large language model applications. The role requires Python programming, familiarity with SQL and analytics platforms, basic cloud knowledge, and the ability to communicate technical concepts clearly while working independently and collaboratively.

Leads the AI product portfolio for fitness apps and connected gym equipment. Responsibilities include managing product managers, defining AI product strategy, prioritizing multi-team roadmaps, owning cross-platform user experiences, partnering with engineering and data teams, establishing responsible AI evaluation practices, and driving adoption and business outcomes. Requires strong product leadership, AI/ML product delivery experience, stakeholder management, and strategic execution in complex organizations.

Lead and develop machine learning, LLM, and automation projects using large-scale network and device telemetry. Clean and transform data, engineer features, build models for anomaly detection, forecasting, and optimization, and deliver reproducible analyses with Python and SQL. Collaborate with engineering and product teams to deploy, integrate, and monitor models in production while contributing to MLOps workflows.

Develop, debug, test, and optimize machine learning models, training pipelines, inference systems, numerical methods, and supporting infrastructure. Build reproducible Python workflows, diagnose computational issues, validate implementations, use coding agents, and document technical findings. This remote role requires approximately 15 hours per week and rapid task availability.