Top Machine Learning Jobs in Hamburg

As a Research Engineer, you'll develop and manage data systems for text-to-speech projects and enhance machine learning models using innovative strategies.

Build Solidgate’s ML/AI function from the ground up, developing real-time payment routing models and production pipelines. Own the full ML lifecycle from experimentation and A/B testing through deployment, while solving modeling challenges involving large-scale transactional data. Partner with Product, Engineering, and Data Platform teams to deliver measurable improvements in conversion, approval rates, losses, and revenue.

Lead development and execution of AI and automation roadmap for Western Europe Amazon e-commerce. Build AI-driven discovery and recommendation strategies, create automated reports and predictive analytics, drive AI tool adoption, ensure responsible AI governance, and run test-and-learn pilots to scale successful e-commerce AI use cases across Amazon markets.

Own the Mapping & Content product domain end to end, including strategy, prioritization, economics, and outcomes. Lead efforts to match hotel rooms and content across suppliers, languages, and formats with high accuracy and coverage. Partner closely with engineering and data science teams on entity resolution, search, matching, catalog, identity, recommendation, and content-quality problems. Identify high-value failures, make trade-offs between precision and coverage, and help build Nuitee’s product organization in a fast-moving environment.

Lead research on interactive avatar models and real-time generative AI video agents. Set research direction, advance multimodal perception and reaction generation, post-train diffusion models, build evaluation frameworks, define datasets, and guide research-to-production efforts. Mentor researchers and influence technical decisions across research, data, and engineering teams.

Own full-cycle recruiting across Mindpeak, focusing on senior, leadership, and hard-to-fill roles in Product, Technology, and Business. Partner with founders and hiring managers to define requirements, source and assess candidates, run rigorous interviews, close hires, and manage external search partners. Improve hiring quality through structured role profiles, scorecards, interview processes, pipeline transparency, and evidence-based talent decisions.

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.

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.

Develop, validate, deploy, and maintain machine learning solutions for medical device manufacturing and CAD/CAM systems. Build deep learning and multimodal AI models using computer vision, 3D geometry, meshes, images, and structured data. Integrate models into production systems, conduct performance analysis, maintain ML workflows, and translate research into practical manufacturing applications while collaborating with engineering, manufacturing, and product teams.

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.

Designs, builds, and maintains scalable data and machine learning infrastructure, pipelines, databases, integrations, self-service tools, and MLOps workflows. The role includes platform expansion, observability, security, data quality, performance optimization, infrastructure as code, CI/CD, documentation, and collaboration with data scientists, analysts, and stakeholders. Strong experience with cloud platforms, Kubernetes, containerization, databases, big data, orchestration, and AI-assisted development is required.

Analyze machine learning model performance, investigate gaps between offline predictions and real-world outcomes, define model and business metrics, and design A/B tests. Build dashboards and automated reports, evaluate statistical significance and business impact, and translate complex findings into recommendations for Data Science, Product, and Business teams. The role also documents reusable analytical methods and challenges technical and product decisions with data.

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.

Build and deploy production machine learning systems for classification, retrieval, ranking, personalization, and evaluation. Develop efficient models and pipelines, improve search relevance and personalization, fine-tune existing models, monitor production performance, debug issues, and ship measurable quality improvements while balancing accuracy, latency, cost, privacy, and reliability.

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.

Optimize large-scale ML inference systems for throughput, latency, cold-start time, and cost per token. Tune SGLang, vLLM, and TensorRT-LLM across GPUs and distributed clusters; improve batching, scheduling, KV caching, quantization, weight loading, JIT caching, and multi-node inference. Profile and instrument systems to validate performance gains, eliminate storage and networking bottlenecks, and establish technical direction through reproducible benchmarks and experiments.

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.

Build and deploy production ML systems for large-scale ecommerce search and recommendations using text, image, and multimodal approaches. Tune and integrate LLMs and transformer models, develop end-to-end visual solutions, improve business KPIs through experimentation, and collaborate across teams to productize and scale ML capabilities.

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.

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.

Designs, develops, and deploys production-grade machine learning systems focused on LLMs, Generative AI, and deep learning. Responsibilities include building scalable ML libraries and research workflows, optimizing distributed training and inference, improving experiment tracking and model lifecycle management, and bridging research prototypes with robust implementations. The role requires collaboration with data science and platform teams, strong software engineering practices, cloud and MLOps expertise, and mentoring across the technical team. Biomedical, clinical, or omics data experience is preferred.

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.