Top Machine Learning Jobs in Cologne

Leads analytical methodology and evaluation for AI-based healthcare and pharmaceutical workflows. Owns model selection, cohort and HCP segmentation, agent decision logic, and evaluation frameworks. Partners with engineering, data architecture, and governance teams to productionize rigorous analytical methods, identify new data and techniques, communicate insights, and mentor data science and engineering colleagues.

Leads data science methodology and advanced analytics for AI-enabled Medical Affairs workflows. Develops and evaluates statistical, machine-learning, NLP, and AI models using healthcare and real-world data; defines validation, monitoring, and decision frameworks; partners with engineering, governance, and business teams to operationalize solutions. Provides technical leadership, mentorship, documentation standards, and strategic guidance while ensuring privacy, compliance, responsible AI use, and clear communication of analytical findings.

Leads ad hoc and exploratory analyses for medical and business questions across a global Medical Insights organization. Prepares and validates datasets, translates ambiguous stakeholder needs into decision-ready findings, and maintains analytical documentation. Tests new data sources, methods, and AI-enabled approaches through proof-of-concept analyses to guide platform investments and roadmap decisions. Partners with business and product stakeholders while supporting compliant, reproducible use of regulated data.

Develop and operate algorithmic trading solutions for European intraday power markets. Responsibilities include market analysis, modeling, backtesting, coding, testing, deployment, monitoring, and performance improvement. The role supports renewable portfolio balancing, platform reliability, and market expansion in Spain, France, and Italy. It involves collaboration with traders and market specialists, plus daytime standby duties on weekends or holidays when needed.

Build and own scalable machine learning and generative AI systems for customer-facing and operational healthcare use cases. Develop production pipelines for training, evaluation, deployment, monitoring, and continuous improvement. Collaborate with product, engineering, data, and business teams; explore emerging AI technologies; define technical roadmaps; and uphold governance, model quality, versioning, observability, and compliance practices.

Develop cloud streaming technology for VDI experiences, focusing on low-latency streaming, graphics, networking, and video codecs. Design, optimize, debug, and maintain C++ software across Windows hardware platforms. Analyze visual quality and responsiveness, collaborate on product requirements and plans, support reliability and observability, and participate in on-call operations while guiding other engineers.

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.

Design, implement, and deploy efficient adaptive machine learning systems that retrain or fine-tune models using production data. The role combines applied research with production engineering, including data strategy, model evaluation, online learning, reinforcement learning, observability, and real-world product development. The engineer will own data products, solve novel technical challenges, and collaborate closely with the founding team on research and product direction.

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.

Develop streaming technology for Windows virtual desktop infrastructure in mixed reality environments. Design, implement, optimize, debug, and profile C++ software across graphics, networking, video, audio, and device integration. Improve streaming quality, responsiveness, reliability, observability, and performance across Windows and Android hardware. Collaborate with stakeholders, create technical designs, guide engineers, manage on-call responsibilities, and resolve production issues.

Lead the architecture, development, deployment, and operation of production-grade machine learning systems for recommendations, personalization, ranking, and product discovery. Translate ambiguous business needs into scalable solutions, oversee the full ML lifecycle, improve reliability and observability, and guide technical decisions. Provide technical leadership through mentoring, design reviews, engineering standards, and collaboration with product, engineering, data, AI, and business stakeholders.

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.

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.

Leads and develops a growing data science team while serving as a hands-on technical expert in machine learning, experimentation, statistical modeling, and model evaluation. Partners with product and engineering leaders to deliver scalable data and AI products, improve measurement practices, guide A/B testing and power analysis, remove obstacles, and strengthen technical standards. Also supports hiring, onboarding, and team capability development.

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 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.

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.

Lead the Agentic Discovery product chapter, initially owning business tooling, dashboards, transparency, and controls for AI-powered commerce experiences. Define strategy, align ML, engineering, design, and go-to-market teams, scale experimentation, launch reliable LLM-powered experiences, and establish metrics tied to usage, conversion, revenue, and engagement. The role will expand to chapter-wide leadership across on-site, offsite, and integrated agentic discovery surfaces.

Designs, builds, and evaluates research prototypes and production-ready systems for portable AI agents, model routing, provider interoperability, memory, retrieval, tool use, and multi-agent workflows. Responsibilities include developing evaluation frameworks, conducting statistically rigorous experiments, creating schemas and APIs, optimizing model and agent systems, and translating research into secure, reliable, reusable components. The role collaborates across research, infrastructure, security, product, and engineering teams and communicates findings through technical reports, benchmarks, demonstrations, open-source releases, and publications.

Designs, builds, and operates production-grade agentic AI systems and orchestration frameworks. Responsibilities include prompt architecture, tool and API integrations, monitoring, evaluation, cost controls, reliability improvements, and governance documentation. The engineer collaborates with data science, data engineering, and governance teams to ensure reliable, compliant workflows using structured healthcare and pharmaceutical data.

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.