Top Machine Learning Jobs in Berlin

Leads an international data science and AI team of up to eight members focused on commercial analytics and AI accelerators. Owns demand intake, prioritization, product strategy, model and data product delivery, and enterprise-scale ML/AI platform development. Partners with commercial, marketing, finance, and brand leaders to translate advanced analytics into business recommendations, revenue growth, and resource optimization. Requires executive communication, team-building, product management, and hands-on expertise in ML, LLMs, agentic workflows, cloud deployment, and pharma or healthcare analytics.

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.

Six-month, onsite internship supporting renewables origination through market research, commercial and client analysis, CRM data management, product strategy, presentations, Salesforce-related automation, and AI-enabled workflow improvements. The intern will generate insights for business development and decision-making, improve operational processes, and coordinate with trading, legal, and operations teams. Business-level English and German proficiency is required, along with quantitative or commercial training and practical data analysis or coding experience.

Lead and develop a team of data analysts within AdTech, transforming reactive reporting into proactive, consultative insights. Own delivery processes, prioritize high-impact projects, manage director-level stakeholders, align analytics roadmaps with ad revenue and vendor ROI goals, and ensure quality across SQL, dashboards, analyses, and machine learning projects. Partner with analysts, data scientists, and engineers to operationalize advanced models while maintaining GDPR compliance and supporting team career growth.

Develop and improve recommendation, ranking, and retrieval models for restaurants, dishes, items, and content. Own applied machine learning problems end to end, including problem framing, data analysis, model development, offline evaluation, experimentation, production deployment, and performance monitoring. Balance relevance with diversity, availability, business constraints, and user intent while collaborating with engineers, product managers, and analysts.

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.

Design and productionize ML systems for advertising using multimodal data (image, video, audio, text, structured). Improve MLOps and data platforms, build scalable data pipelines, monitor models, collaborate cross-functionally, and drive team processes and product impact.

Design, build, and productionize machine learning solutions on AWS. Work end-to-end from data exploration, feature engineering, modeling, and evaluation to packaging, deploying, monitoring, and iterating models (including LLM/GenAI workflows). Collaborate with engineers, product partners, and data scientists to deliver reliable, reproducible ML systems and move prototypes into scalable production.

Lead FP&A for Germany: develop and maintain financial planning, controls, reporting, budgeting and forecasting. Manage FP&A team, financial analysis, valuation models, stakeholder partnering, and drive automation, digitization and multi-dimensional data models to enable reliable financial decision-making.

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.

Design and implement automations and scalable workflows; work with data and automation tools; build autonomous agent systems for pricing, market analysis and forecasting; manage projects end-to-end; design data architectures and maintain clear documentation to deliver measurable business impact.

Leads Zendesk’s EMEA Sales Engineering organization, driving enterprise market expansion, technical win rates, proof-of-concept standards, and customer adoption. Recruits and develops sales engineering leaders, partners with regional sales executives, and serves as a technical evangelist for AI-powered customer experience solutions. The role requires executive presence, public speaking, enterprise architecture expertise, cloud and integration knowledge, and strong understanding of generative AI, LLMs, and CX technologies.

Lead product strategy and roadmap for Search and Discovery, building AI/ML-driven relevance, intent understanding, ranking, personalization, and experimentation. Partner with Engineering, Data Science, Design, and Commercial teams to deploy and optimize ML models, run A/B tests, and translate customer insights into measurable product outcomes. Communicate vision to stakeholders and embed search capabilities across the customer journey.

Analyze complex datasets, develop predictive models and machine learning algorithms, collaborate with data teams, communicate findings, and support data-driven solutions for clients.

Conduct large-scale molecular dynamics and free energy simulations for protein-ligand and protein-membrane interactions. Build reproducible Python workflows and machine learning-ready scientific datasets using distributed computing infrastructure. Collaborate with computational biologists, machine learning researchers, and engineers to integrate simulation outputs into biomolecular models. Validate results against reference calculations and experimental data, assess uncertainty and convergence, and independently lead research projects producing novel methods, publications, datasets, and software.

Lead and manage a team of solution architects and consultants to design and deliver AI-driven digital transformation programs across Germany and Austria. Provide architectural direction for AI, data platforms, analytics, IoT, and application modernization; ensure secure-by-design and cloud security practices; coach and grow the team; and support strategic customer engagements and delivery execution.

Lead the design and delivery of a greenfield Anti Financial Crime platform: define product roadmap and architecture, translate AML/AFC requirements into technical specs, partner with AML/Ops and engineering to build detection/prevention tooling, integrate controls across products, and drive agile, high-velocity releases with strong stakeholder alignment.

Senior AI/ML Consultant focuses on transforming AI ambitions into production-ready systems, guiding clients through the AI integration process and building operational AI strategies. The role includes leading projects, mentoring junior staff, and contributing to thought leadership in Data & AI.

Own an AI investing product vertical end-to-end, including strategy, metrics, roadmap, technical design, delivery, and launch. Partner with engineering on APIs, data flows, ledgering, reliability, security, and scalability. Incorporate KYC, transaction monitoring, privacy, licensing, and regulatory requirements. Apply AI with robust evaluation, safeguards, human oversight, and failure handling. Coordinate Engineering, Design, Compliance, Operations, Treasury, and Finance to deliver reliable, auditable financial products.

Build, deploy, and scale Bayesian MMMs and econometric/time-series models to measure marketing impact. Engineer reproducible, production-grade model pipelines, automate validation and health monitoring, and translate model outputs into business decisions while partnering with marketing leadership.

The AI Product Manager will drive the development of AI-powered applications, collaborating with engineering and design teams, conducting market research, and optimizing AI models to align with user needs.

As a Principal Software Engineer, you'll lead multiple teams in Risk Management, designing cloud-based solutions, mentoring engineers, and driving innovation.

Lead and scale Feedzai's EMEA partner ecosystem (GSIs, OEMs, acquirers, processors, hyperscalers, ISVs). Drive partner strategy, joint go-to-market, partner-sourced revenue, onboarding/enablement, KPIs and reporting, and support joint marketing and demand-generation activities.

Develop and integrate reinforcement learning agents into autonomous aerial systems, ensuring reliability and performance. Collaborate with teams and enhance the software stack while mentoring peers.

Own day-to-day execution of the SAP partnership across technical, research, and commercial workstreams. Track commitments, coordinate engineering and research capacity, support joint scoping, co-selling, pricing, packaging, and commercial terms, and maintain accurate partnership records. Onboard SAP stakeholders, identify stalled initiatives, escalate delivery-capacity risks, and help build scalable partnership processes, playbooks, and templates.