Top Machine Learning Jobs in Cologne

CrowdStrike seeks a Senior Intelligence Analyst to provide threat intelligence and digital risk monitoring, collaborating with teams to deliver customer-focused solutions and presentations, while maintaining customer relationships.

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.

Own positioning, messaging, and go-to-market for SaaS and DaaS products. Lead product launches, translate market and customer insights into commercial strategies, support sales enablement, influence product strategy, and collaborate cross-functionally across international teams to drive adoption and revenue.

Lead AI and machine learning architecture, mentor teams, drive innovation, and evaluate tools for AI systems development across global teams.

Manage various AI/ML projects from concept to development, coordinating teams, managing risks, and ensuring project goals are met. Responsible for documentation and financial planning.

Lead a delivery lane for forward-deployed AI engineering, hire and manage a decentralized team, drive production ML/AI automation (50% hands-on), standardize templates/skills, and coordinate stakeholders to accelerate domain onboarding and business impact.

Lead global marketing strategy and GTM to scale Aisle into a market leader. Own brand, PR, product positioning, full-funnel demand generation, ABM, marketing tech stack, RevOps, attribution, budget/agency management, and grow a multidisciplinary marketing team aligned to revenue targets.

Test native iOS and Android photo-editing apps (manual and automated), validate image-processing and ML features, design/maintain automated test suites, perform exploratory testing, use AI-assisted tools for test generation and analysis, report QA metrics, collaborate with cross-functional teams, and create testing documentation.

Drive independent, high-impact research on frontier AI topics, publish findings, collaborate widely, and mentor new researchers in the field.

Lead analytics engagements for financial services and payments: analyze large datasets, build statistical and machine learning models for credit risk, fraud, and customer behavior, support pre-sales and proof-of-concepts, collaborate with Sales/Product/Marketing to integrate solutions, and strengthen client relationships to identify new business.

Develop, design, test and implement imaging and 3D reconstruction algorithms using C++ and Python. Analyze real data, optimize for high-performance computing, integrate algorithms into applications, and collaborate across algorithms, physics, and electronics teams while participating in design and code reviews.

Lead product strategy and roadmap for query interpretation and search quality. Own models, tools, and metrics to optimize recall and precision. Collaborate with ML, infra, and product teams, triage quality issues, benchmark competitors, and build evaluation frameworks and explainability for search results.

Lead the Recommendations engineering team to build scalable, reliable recommendation-as-a-service products. Own recommendation quality and business impact, set technical direction, translate product goals into engineering plans, ensure SLAs, hire and coach engineers, and drive system reliability and scalability.

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.

Own post-sale customer lifecycle for Portuguese utility accounts: onboard, embed Neara into workflows (vegetation management, clearance analysis, CAPEX), run QBRs, monitor health scores, drive renewals and upsell, and align product roadmap with local market needs.

The AI Lead Product Manager will define and own the product strategy for AI-powered health data, lead product teams, engage with stakeholders, and ensure compliance with regulations.

Own Go-To-Market for performance media buyers: build relationships, close and onboard clients, represent Kayzen at industry events, advise prospects on product strategy, and funnel market feedback across 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.

The Senior Software Engineer will develop AI-powered recruiting products using Python, manage microservices, build RESTful APIs, and collaborate with teams on scaling applications.

Support sales by conducting technical discovery, delivering customized demos and POCs, designing solutions with customers, responding to RFIs/RFPs, coordinating internal teams, answering security questionnaires, and acting as a trusted advisor on fraud/AML and financial crime prevention.

Lead and deliver petrophysics, seismic petrophysics and rock physics consulting projects and training. Develop best-practice workflows, support sales with technical proposals, publish and present technical work, and build customer relationships to grow consulting services and software adoption.

The Head of Education & Community at Siena is responsible for developing product education, onboarding programs, community events, and market education resources. This role involves creating curricula, conducting workshops, and supporting sales with training and demos while leveraging AI for teaching efficiency.

The role involves driving new AI software sales, engaging with executives, and leveraging industry expertise to close large enterprise deals.

The role involves integrating AI tools into .NET and C++ applications, optimizing models for performance, and collaborating with engineers on deployment and monitoring.

The role involves designing and developing model evaluation pipelines, user studies for subjective evaluations, and automated dashboards to report results, alongside leading the evaluation team and communicating with other teams to improve model performance.