Top Machine Learning Jobs in Berlin

Apply machine learning and generative AI systems to extract clinically relevant information from oncology records. Validate AI-generated datasets, analyze model and dataset performance, define training and evaluation requirements, support data product development, and collaborate with clinicians, researchers, engineers, and international stakeholders to productionize and monitor models used in cancer research.

Develops and integrates radiating components and passive radiation-pattern structures for multiband base-station antennas. Responsibilities include 3D and 2D electromagnetic simulation, prototype RF measurements, performance optimization, troubleshooting, technical documentation, and supporting the product lifecycle through mass production. The role collaborates with international cross-functional teams and requires relocation to Rosenheim, Germany.

Lead the vision, roadmap, architecture, and execution strategy for a centralized machine learning platform at a digital bank. Own enterprise MLOps infrastructure, model evaluation, monitoring, governance, and high-volume real-time decisioning for fraud, credit risk, and operations. Partner with engineering, data science, security, legal, and regulatory stakeholders while mentoring product managers and establishing platform standards.

Develop and scale LLM-powered virtual assistants and agentic support systems. Build autonomous resolution and decisioning models, implement RAG and other GenAI techniques, establish evaluation and safety guardrails, and deploy models in low-latency production environments. Collaborate with engineering, product, decision science, and support teams to improve automation, containment, and customer satisfaction through experimentation and data-driven solutions.

Drive strategy and execution for N26’s Customer Risk Lifecycle and Anti-Financial Crime initiatives. The role develops KPIs, analyzes workflows and performance data, improves processes through automation, manages vendors, builds business cases, and coordinates cross-functional projects across Product, Technology, Data, Finance, and Growth. It also supports compliance-related initiatives, customer risk optimization, operational scalability, and business resilience.

Lead an international risk analytics team focused on credit solvency and fraud risk. Drive data-driven risk strategies, monitoring, reporting, pricing insights, process improvements, and advanced analytics. Partner cross-functionally with Risk, Data Science, Pricing, Finance, Sales, and Operations teams, while enabling machine learning models and representing risk analytics in strategic projects.

Designs and maintains enterprise integrations across SaaS platforms, cloud infrastructure, data systems, and internal applications. Builds GitLab CI/CD pipelines, Terraform-based AWS infrastructure, automation workflows, APIs, event-driven data pipelines, and AI-enabled middleware using Node.js or Python. Manages MCP servers, integrates machine learning and LLM services, troubleshoots system performance, and ensures secure, reliable, well-documented solutions through collaboration, testing, and continuous improvement.

Build and deploy production machine-learning models predicting user value, engagement, and reward behavior. Design A/B tests and apply causal reasoning to evaluate offers, rewards, and ranking. Develop data infrastructure and measurement systems for rigorous impact analysis. Own ambiguous product problems from ideation through production while working with Python, SQL, and AI tools. The role emphasizes research depth, independent problem-solving, and rapidly shipping models that influence millions of users.

Design and lead large-scale biomolecular experimental data-generation campaigns for Microsoft’s BioEmu models. Responsibilities include selecting assays and systems, directing CROs and collaborators, reviewing data quality, diagnosing experimental artifacts, building traceable machine-learning datasets, and coordinating computational and experimental research. The role requires independent research ownership, strong quantitative and biophysical reasoning, cross-disciplinary communication, and experience with biological, structural, or biophysical datasets.

Develop, validate, and deploy computer vision and machine learning algorithms for clinical decision support using imaging and sensor data. Own projects from messy data and modeling through rigorous evaluation and production integration. Collaborate with hardware, software, medical, and clinical research teams, apply classical and deep learning methods, support regulatory readiness, deliver production-quality Python code, and mentor colleagues.

Lead the ML product roadmap for speech and NLP, convert customer feedback into prioritized ML work, define model evaluation gating, partner with engineering leads to ship production improvements, and own ML product KPIs to drive measurable user impact.

Legal Counsel will advise Quince’s UK and EU operations across commercial contracts, employment, privacy, consumer protection, AI governance, technology, logistics, product compliance, intellectual property, and risk. The role independently owns legal matters, builds processes and playbooks, supports international expansion, manages external counsel, monitors regulatory developments, and provides pragmatic guidance to cross-functional teams in a fast-growing technology-led retail business.

Leads Tide’s KYX engineering organization across onboarding, continuous due diligence, identity and access, risk scoring, data science, and machine learning. Owns engineering strategy, organizational design, model lifecycle, regulated AI deployment, platform scalability, and global execution. Partners with operations, policy, risk, compliance, product, and regulators to improve onboarding conversion, decisioning automation, due diligence quality, and servicing economics.

Own and expand strategic enterprise accounts across Europe, serving as executive relationship owner and driving revenue growth through account expansion plans. Coach account managers and customer success teams on strategy and complex commercial execution, improve key account processes, collaborate with product and customer operations, and report performance and pipeline to leadership. Represent the company with utility customers at conferences and events.

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 vision, strategy, and roadmap for Flix Search across web, app, and AI-native channels. Lead discovery and delivery of improvements to ranking, relevance, query understanding, personalization, comparison, and zero-result recovery. Use behavioral, funnel, query, and customer data to guide decisions, align cross-functional stakeholders, and balance near-term enhancements with long-term technical investments. Partner closely with engineering, UX, data, commercial, and operations teams to improve conversion and create scalable discovery experiences.

Paid 12-week summer internship supporting Databricks platform product teams. The intern will help build features, manage projects end-to-end, analyze product usage, make data-driven decisions, and communicate complex topics to engineering, customer, and field partners. The role offers mentorship and exposure to data and AI infrastructure across areas such as machine learning, SQL, ETL, streaming, and content organization.

Leads a multinational BDR organization of approximately 18 representatives through team leaders. Owns BDR strategy, playbook development, performance management, metrics, sales technology adoption, process optimization, and cross-functional alignment with Sales, Marketing, and senior leadership. The role combines strategic planning with hands-on operational leadership across European and US markets, driving scalable prospecting, qualification, conversion, and team development.

Build data warehouses, cloud infrastructure, AI workflows, and scalable data products. Integrate data from multiple systems, enable organizational data access, assess AI use cases, and collaborate with analytics, product, and software engineering teams in an agile environment.

Lead product vision and discovery for a genomics-driven diagnostic and personalization platform. Validate hypotheses with patients, clinicians, and partners; translate research into product specs; coordinate labs and data providers; partner with engineers and researchers to build AI prototypes; shape data, regulatory, and GTM strategy while making core product and architectural decisions.

Leads the design, development, deployment, and evaluation of machine learning, forecasting, recommendation, and analytical solutions. Partners with Product, Commercial, Engineering, and Data teams to solve business problems, define metrics, build scalable pipelines, and deliver measurable impact. Provides technical leadership and mentorship, promotes model development and governance best practices, and contributes to the data science roadmap.

Develop data science solutions for performance marketing, including marketing mix modeling, incrementality testing, causal inference, predictive modeling, creative analytics, and campaign optimization. Build scalable data products and pipelines with Data Engineering, guide Applied AI model deployment and impact analysis, and shape the experimentation roadmap. The role requires strong SQL and Python skills, advanced communication, and experience in B2C performance marketing, marketplaces, machine learning, and experimentation.

Lead product strategy for Lounge's marketing platform: own data hubs, messaging (Braze), automation, ML/LLM-driven marketing agents, compliance-by-design, vendor integrations, and roadmap. Mentor PMs and align engineering, commercial, and privacy requirements to drive autonomous, revenue-generating marketing.

Own end-to-end data science initiatives for credit risk and fraud, including problem framing, data pipelines, modeling, deployment, monitoring, and business adoption. Build fraud detection, anomaly detection, credit scoring, transaction decisioning, and limit-management models. Partner with Engineering, Risk, Compliance, Finance, and Payments to make defensible decisions, explain trade-offs, and deploy reliable production systems. Use and evaluate AI coding tools while maintaining strong testing, documentation, and operational standards.

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.