Top Machine Learning Jobs in Munich

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.

Own the strategy, roadmap, metrics, and adoption of JetBrains Context, a managed retrieval layer for AI coding agents. Partner with engineering, ML, platform, IDE, marketing, sales, and customer success teams to improve indexing, retrieval quality, integrations, reliability, cost, and latency. Define product direction, evaluate competitors, establish quality metrics, communicate with customers and developer communities, and drive enterprise adoption.

Own backend and infrastructure for AI shopping agents, including live checkout automation, large-scale product ingestion, search and ranking, deployments, monitoring, databases, and on-call operations. Build reliable systems that handle changing retailer environments, real payments, and continuously evolving catalogs. Work closely with the CTO in a fast-moving environment.

Lead operations-focused consulting engagements end-to-end, drive problem-solving and recommendations, manage teams, apply analytics and digital solutions, build client relationships, and support sustainable operational transformation.

Conduct research on failure management in optical transport networks using machine learning. Review existing research, investigate algorithms for data generation and failure prediction, present findings, and prepare a final report. The three-month internship offers mentorship, collaboration with optical networking experts, and potential continuation into a master’s thesis.

Develop machine learning and analytics solutions using large-scale datasets. Responsibilities include feature engineering, predictive modeling, workflow optimization, customer implementations, production deployments, stakeholder collaboration, technical training, and resolving data-related challenges. The role requires Python, PySpark, machine learning pipelines, MLflow or Airflow, statistical modeling, and strong communication skills, with preferred experience in fraud detection, risk analytics, compliance, cloud environments, and model monitoring.

Lead data science and credit risk strategy across Southeast Asia. Build and oversee production machine learning models for underwriting, fraud detection, risk segmentation, and real-time decisioning. Establish credit policies, monitor portfolio performance, lead stress testing, and support responsible market expansion. Build and mentor data science and risk teams while partnering with engineering, product, finance, and executives to improve approvals, defaults, time-to-decision, and unit economics.

Generate profitable public-sector revenue in Germany by selling cybersecurity solutions through channel partners. Achieve quotas, manage opportunities, support renewals, engage customers, maintain CRM and forecasting accuracy, provide quotes, and communicate Sophos’s value proposition. The role requires IT solution sales experience, channel ecosystem knowledge, negotiation and presentation skills, strong telephone sales abilities, fluent German, and legal authorization to work without employer sponsorship.

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

Leads strategic R&D engagements from presales through delivery, translating scientific and business challenges into AI architectures, product backlogs, MVPs, simulations, integrations, data pipelines, and production solutions. Builds trusted relationships with R&D executives, scientists, engineers, and technical teams; assesses data, compute, feasibility, value, staffing, and delivery plans. Develops reusable architectures and playbooks, oversees technical workstreams, evaluates emerging AI capabilities, and provides feedback to shape Microsoft Discovery products and scalable industry solutions.

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.

Owns full-cycle recruiting for commercial, operational, and technical roles across global markets. Responsibilities include sourcing passive candidates, building pipelines for hard-to-fill positions, advising hiring leaders, coordinating interviews and offers, maintaining accurate Greenhouse data, and improving hiring processes through systems thinking, data, AI, and automation.

Lead system-level architecture for a first-of-a-kind stellarator power plant, integrate plasma, magnets, cryogenics, and controls; close design loops with subsystem teams, quantify model uncertainties, run first-principles and reduced-order studies, and turn analyses into actionable engineering decisions to optimize performance, margin, and cost.

Design legal AI tasks, datasets, workflows, and evaluation rubrics; assess system outputs for legal accuracy and usefulness; translate legal processes into agentic workflows; lead enterprise pilots and implementations; and support customer discovery, demonstrations, and go-to-market initiatives. The role requires close collaboration with AI researchers and engineers and offers broad ownership in an early-stage company.

Develop research methods and systems for matter-specific legal AI, including model and agent adaptation, data curation, benchmark design, training, inference, experimentation, and evaluation infrastructure. Collaborate with founders, engineers, legal experts, and enterprise partners to translate legal workflows into agentic systems and production capabilities. Help shape the company’s technical direction and research culture while owning empirical research and engineering projects end to end.

Own the Vault product roadmap and lifecycle for a sports media asset platform. Lead discovery with customers, define solutions for content ingest, storage, integrations, AI enrichment, metadata, search, rights, and asset monetization. Partner closely with engineering, sales, and customer success, attend customer events, and prioritize product bets that help sports organizations maximize the value of extensive media archives.

Corti is seeking passionate individuals to join their talent community, shaping the future of healthcare through AI technologies. Opportunities include roles in AI technology, machine learning, and software development, focusing on reducing errors and improving patient outcomes.

Leads the transformation of translational and biomarker data into standardized, AI-ready data products for drug discovery and development. Oversees data standards, catalogs, metadata, harmonization, quality frameworks, APIs, automation, and enterprise integration. Manages a distributed team of 12–15 data stewards and engineers, establishes multi-year strategy, coordinates cross-functional stakeholders, oversees budgets, and advances FAIR data practices, governance, and AI-enabled workflows across therapeutic areas and research partners.

Leads a distributed team transforming translational and biomarker data into standardized, FAIR-compliant, AI-ready data products. Responsibilities include defining data standards, metadata, semantic schemas, quality frameworks, APIs, and integration with enterprise data platforms. The role delivers analysis-ready datasets for precision medicine and biomarker discovery, automates curation and quality assurance, establishes multi-year data roadmaps, coordinates global stakeholders, manages budgets, and advances data governance across labs, studies, therapeutic areas, and partners.

Drive enterprise SaaS revenue growth across Central Europe, focusing 90% on new business. Prospect, develop, manage, and close complex opportunities with B2B organizations; build territory, account, and opportunity plans; exceed quotas; and sell Conga’s revenue management solutions. Collaborate with sales engineering, marketing, customer success, partners, and professional services while presenting tailored solutions, managing the full sales cycle, and cultivating strategic relationships.

Build and improve Firefox WebCompat internal dashboards, reporting tools, and broken-site screenshot capture pipelines. The role involves creating reliable data views for triage and metrics, automating screenshot workflows, collaborating with WebCompat and QA teams, and translating reporting needs into effective tooling. Familiarity with WebCompat workflows, Bugzilla, screenshot automation, and machine learning is preferred.

Research and develop GPU-accelerated techniques for AI, deep learning, machine learning, and HPC workloads. Analyze and optimize complex algorithms across CPU and GPU architectures, perform low-level performance tuning, publish optimization techniques, and collaborate with hardware, software, research, and developer communities to influence future architectures and programming models.

Build and operate inference services and APIs for production world models. Responsibilities include deploying research models, optimizing GPU utilization, memory, batching, cold starts, reliability, and cost at scale. Collaborate with research and product teams to deliver new AI capabilities and customer-specific configurations. Requires strong Python, production API ownership, containerized GPU services, and hands-on inference performance optimization.

Lead data strategy, architecture, governance, quality, compliance, and technology adoption. Translate stakeholder needs into scalable data initiatives, support advanced analytics and AI/ML, promote data literacy, and guide cross-functional teams toward data-driven decision-making.

Build quantum sensing and magnetometry capabilities using NV centres, optically pumped magnetometry, modelling, experimentation, and machine learning. Characterise sensing systems, develop digital twins, improve calibration, investigate biomagnetic and industrial applications, support patents and commercialisation, publish research, pursue grants, collaborate with faculty, and supervise student projects. The role combines hands-on experimental physics with modelling and applied outcomes.