Top Machine Learning Jobs in Germany

Own the full sales cycle for technically complex B2B deals involving APIs, on-premises deployments, and custom licensing. Manage multi-stakeholder negotiations, build strategic customer relationships, drive retention and expansion, and develop sales processes in an early-stage environment. Collaborate with engineering, research, product, solutions engineering, and legal teams while translating customer needs into product feedback.

Own end-to-end talent acquisition and headhunting for Arago’s technical hiring across France, North America, and Israel. Partner with the CEO, CTOs, and engineering leaders to define roles, source and close senior engineers, scientists, and technical leaders across hardware, optical, software, and research. Build proactive sourcing pipelines, improve interview processes and hiring standards, monitor pipeline health and hiring velocity, and communicate progress to leadership.

Identifies, designs, deploys, and sustains AI solutions within a Wind Engineering subsystem. Partners with engineering leaders to prioritize use cases, integrates AI into engineering workflows, ensures governance and cybersecurity compliance, drives adoption, and monitors solution performance and value. The role develops applications, agentic workflows, copilots, automation, predictive models, and knowledge systems while contributing reusable patterns and innovations to the broader AI community.

Leads the identification, design, deployment, integration, governance, adoption, and continuous improvement of AI solutions across a Wind Engineering subsystem. Partners with engineering and business leaders to prioritize AI use cases, build roadmaps, configure AI applications and agentic workflows, integrate solutions into engineering processes, validate outputs, ensure security and responsible AI compliance, educate teams, and monitor solution performance and business value.

Develop motion planning, decision-making, vehicle control, and estimation algorithms for autonomous vehicles. Implement mission-critical real-time C++ for embedded automotive systems, build simulation and analysis tools in Python and C++, integrate with perception and platform teams, validate software on vehicles, define safety and performance metrics, analyze field data, and implement safety mitigations.

Designs and develops large-scale SAP software solutions for financial consolidation, planning, forecasting, reporting, and performance management. Maintains ABAP code and builds SAP HANA, BPC, SAC, Fiori, and PaPM components. Integrates Google Cloud, AI/ML, and Python models with SAP platforms. Collaborates with architects, engineers, product owners, and finance stakeholders while ensuring reliability, testing, compliance, audit readiness, and regulatory alignment across the software lifecycle.

Own production optimization of LLM and VLM inference systems, improving latency, throughput, memory efficiency, GPU utilization, quality, reliability, and cost. Deploy and benchmark inference engines, build compression and quantization workflows, implement acceleration techniques, diagnose serving bottlenecks, and collaborate with kernel, platform, research, product, and customer teams.

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.

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.

Build end-to-end machine learning systems spanning research reproduction, model evaluation, inference infrastructure, backend services, and product interfaces. Design rigorous experiments, evaluation datasets, and verification workflows; analyze model internals; investigate provenance and evasion; and convert findings into reliable production systems with APIs, background jobs, observability, testing, documentation, and user-facing React/TypeScript experiences.

Develop and maintain high-load, real-time personalization services for global e-commerce platforms. Improve shopper experiences and business KPIs through applied machine learning, user interaction modeling, personalization and recommender systems, hypothesis validation, and A/B testing. Collaborate with engineering teams and business stakeholders to research, deliver, and communicate personalization capabilities and outcomes.

Build and maintain high-performance differentiable simulation software for open and closed quantum systems using Julia and Python. Develop model-learning, parameter-inference, neural-network PDE-solving, and optimisation methods. Benchmark research methods, improve performance and reliability, collaborate with university faculty, publish results, supervise students and interns, and contribute to teaching materials.

Lead complex enterprise customer engagements as the senior technical authority for data and AI strategy. Drive Databricks adoption, consumption, competitive displacement, and revenue growth through architecture, migrations, streaming systems, lakehouse platforms, and AI/ML solutions. Manage executive relationships, orchestrate cross-functional teams, mentor solutions architects, develop competitive strategies, and contribute to technical thought leadership. Weekly travel is required.

Lead and grow a multidisciplinary digital toxicology team in Frankfurt to develop AI/ML and QST models, integrate computational tools across preclinical safety workflows, build AI-ready data foundations, modernize the digital toxicology toolkit, and drive cross-functional adoption and regulatory-aligned in silico approaches.

Lead end-to-end architecture, implementation, and delivery of Blue Yonder Warehouse Management and related execution solutions. Serve as the primary client contact, manage timelines, budgets, risks, and deliverables, and lead solution teams and integrations. Provide functional and technical guidance, mentor junior staff, align solutions with business objectives, and collaborate with project managers, delivery partners, and stakeholders to deliver successful client outcomes.

Leads and grows a distributed EU-based AI and Machine Learning team, managing Data Scientists and Machine Learning Engineers. Responsibilities include line management, coaching, performance reviews, team culture, delivery processes, engineering quality, CI/CD, cloud automation, monitoring, architecture discussions, process improvement, and cross-regional stakeholder collaboration. The role partners with AI leadership on technical, organizational, and HR matters.

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, 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.

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.

Own the end-to-end architecture for an EMAT flow sensor spanning hardware, embedded software, AI, signal processing, and cloud applications. Guide cross-functional development teams, translate product and customer requirements into technical specifications, ensure regulatory compliance, and lead system integration and testing. Serve as a technical contact for customers and stakeholders while supporting agile collaboration across international teams.

Develop and optimize machine learning models for understanding and generating 3D CAD parts. Build CAD data pipelines, implement geometric deep learning workflows, deploy models to production, improve performance, and collaborate with product and engineering teams. The role requires Python, PyTorch or TensorFlow, 3D data representation expertise, ML engineering practices, and experience productionizing models. CAD software, computational geometry, and MLOps experience are preferred.

Lead GTM operations across EMEA and APAC by developing commercial growth strategies, forecasting frameworks, territory plans, sales methodologies, dashboards, and pipeline management processes. Partner with executive leaders across Sales, Finance, Marketing, Customer Success, and Partnerships. Use Salesforce, Outreach, Snowflake, AI, and machine learning to improve forecast accuracy, pipeline conversion, reporting automation, and sales productivity.

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.

Architect and implement agentic AI solutions for semiconductor applications, including multi-agent systems, reasoning, planning, and reinforcement learning workflows. Collaborate with hardware, software, and data teams to deploy scalable, usable AI applications. Evaluate emerging agent-based AI technologies and apply them to semiconductor manufacturing challenges. The role also involves AI/ML development, web front-end integration, cloud platforms, MLOps, and continuous adaptation to evolving technologies.

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.