Top Machine Learning Jobs in Cologne

Design, develop, deploy, and operate production-grade machine learning systems for retail media, including sponsored product ranking, audience segmentation, campaign optimization, attribution, and performance measurement. Build scalable ML pipelines, monitor model performance, ensure reliability, and communicate technical decisions to product, engineering, and commercial stakeholders. Contribute to engineering standards and knowledge sharing.

Own the Smart Risk Engine for a B2B mobility and payments platform. Develop statistical, machine learning, and AI models; build cloud-based end-to-end ML pipelines; manage training, calibration, backtesting, monitoring, drift detection, and explainability. Create credit-risk use cases including early-warning systems, loss databases, exposure steering, and portfolio insights. Partner with senior stakeholders, translate analytics into business recommendations, and mentor Data Scientists. German and English fluency are required.

Manage and expand enterprise accounts across the EMEA region through consultative selling, strategic account planning, renewals, customer retention, and new business development. Build relationships with senior executives, sell complex software and analytics solutions, maintain CRM records, monitor market trends, and collaborate with Customer Success, Marketing, SDRs, and Product teams. German and English fluency are required, with travel to events and customer meetings.

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.

Partner with universities, research labs, and faculty to drive adoption of NVIDIA accelerated computing and AI technologies. Integrate NVIDIA frameworks, libraries, GPUs, CPUs, networking, and software into scientific workloads at supercomputing scale. Lead research collaborations, trainings, workshops, lectures, and demonstrations; mentor researchers; track emerging trends; develop prototypes; and provide feedback to NVIDIA Engineering. Support publications, conference presentations, and technical content while serving as a trusted technical advisor.

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.

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.

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 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 and expand a strategic financial-institution account across the DACH region. Build C-suite relationships, identify business challenges, develop tailored enterprise solutions, structure and negotiate multi-million-dollar SaaS deals, and execute joint business plans to achieve growth and profitability targets. Act as the client advocate internally, influence product strategy, collaborate across sales and delivery teams, and serve as a trusted advisor on analytics, fraud, risk, lending, and decisioning technologies. Travel may reach 50%.

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.

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, 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.

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 the strategy, design, deployment, and scale-up of AI-powered health products across the Global South. Own product roadmaps, execution, government-system integration, stakeholder adoption, partnerships, grant development, and portfolio expansion. Collaborate with engineering, machine learning, program, and domain teams to deliver sustainable, measurable public-health impact.

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.

Architect and build the AI layer for Neo4j’s Hume Maestro platform. Responsibilities include setting the AI technical roadmap, contributing hands-on to production code, designing scalable AI architectures, establishing model evaluation and deployment practices, integrating AI with front-end and platform systems, and collaborating with Product and Science stakeholders. The role may eventually evolve into leading and mentoring a dedicated AI engineering team.

Lead end-to-end marketing strategy for DACH Public Sector to boost AI perception, generate high-value demand, run account-based programmes, manage events, vendors and agencies, and align campaigns with sales and policy stakeholders.

Own full-cycle recruiting for technical roles, partner with hiring managers to define roles, source and close candidates, build scalable systems and pipelines, optimize hiring with data, and support a global, remote people team while acting as a culture ambassador.

Lead Rasa’s product organization and define strategy for its enterprise conversational AI platform. Manage and develop a team of product managers, own product roadmaps and lifecycle decisions, and partner with engineering, sales, and marketing on product definition, pricing, packaging, and go-to-market. Use customer research, market analysis, competitive intelligence, and developer feedback to guide innovation and foster a strong ecosystem across cloud, on-premises, and open-source deployments.

Lead and build Solidgate's ML/AI function from scratch: define vision and architecture, hire and lead the team, deliver real-time decisioning and recommendation systems, partner with Product/Engineering/Data Platform, run experiments and A/B tests, and translate models into revenue-driving production features.

The Data Scientist will design algorithms for insights, structure data, collaborate with machine learning engineers, and analyze datasets to improve workflow automation and product value.

Assess and evaluate AI-generated technical content, craft and answer advanced ML/AI questions, identify errors and hallucinations, rank responses by correctness and clarity, and provide precise feedback to improve model performance.

The Applied Scientist will solve impactful problems using deep learning models and statistical analysis, translating commercial goals into technical solutions.