Top Machine Learning Jobs in Berlin

Work with AAA developers to optimize GPU/system performance for path-traced and neural rendering, develop and tune neural rendering algorithms and AI models, profile and optimize low-level performance, collaborate with architecture and driver teams, and create demos, papers, and presentations for conferences.

Lead Data, Analytics, AI, and GenAI presales activities for strategic enterprise opportunities. Facilitate discovery workshops, translate business needs into scalable architectures, lead RFP and RFI responses, and present solutions to executives. Design end-to-end AI and cloud architectures across Azure, GCP, Databricks, and open-source ecosystems. Advise on AI transformation use cases, roadmaps, governance, and implementation, while mentoring delivery teams and developing reusable frameworks, offerings, thought leadership, and customer success materials.

The Consulting Manager will lead AI transformation programs, work with executives on strategy, drive business growth, represent the company in discussions, and mentor teams.

As an Enterprise AI Adoption Manager, you will guide companies in adopting AI, manage enterprise accounts, drive AI transformation, and work closely with engineering and product teams to deliver value.

The Senior Data Product Manager drives product maturity and strategic growth at Seqana by translating user needs into technical requirements, overseeing product lifecycles, and exploring market opportunities.

Lead the development of large language models for marketing technologies, optimize AI solutions, and mentor junior team members to drive innovation and quality.

Leads digital transformation across procurement by implementing and optimizing SAP, Coupa, ERP, e-sourcing, and supplier management technologies. Oversees data governance, integration, process improvement, category and spend analytics, supplier performance monitoring, and cross-functional project delivery. Evaluates emerging capabilities such as AI and RPA, manages stakeholder relationships, mentors team members, and drives procurement technology innovation and operational efficiency.

The AI Business Development Specialist will identify business opportunities, build client relationships, and promote AI solutions in various sectors, with a focus on the MENA region.

Lead AI and machine learning architecture, mentor teams, drive innovation, and evaluate tools for AI systems development across global teams.

Build Solidgate’s new ML/AI function, developing production machine learning models, recommendation systems, and real-time transaction-routing decision systems. Own experimentation from ideation through A/B testing and deployment, engineer features from high-cardinality transactional data, integrate emerging AI technologies, and collaborate with Product, Engineering, and Data Platform teams on training and analytics pipelines.

Lead finance transformation and pre-sales solution architecture for Workday Financials. Design end-to-end multi-country FIN solutions, lead workshops, drive executive alignment, enable sales, and shape post-go-live roadmaps using AI/automation to modernize finance operations.

Own machine learning projects from exploration through production, building reliable agentic LLM systems for clinical settings. Develop evaluation datasets, offline and online testing harnesses, LLM-as-judge workflows, regression tests, and production feedback loops. Improve models through prompting, retrieval, distillation, and fine-tuning. Partner with product, clinical, and engineering teams, while reviewing code, sharing knowledge, and mentoring junior engineers.

Research and investigate global fraud trends using BioCatch data and external sources. Produce data-driven insights, visualizations, written thought leadership, dashboards, and presentations. Build repositories and automate analysis workflows while applying fraud expertise and AI tools to validate findings and support sales and marketing.

Develop core methods for temporal ontology extraction and contradiction detection. Collaborate with research teams and publish findings. Prototype ideas, create datasets, and validate methods.

Lead design and development of scalable front-end applications using React and TypeScript for an AI/ML-powered cloud-native SaaS platform. Collaborate with product, UX, backend, and ML teams to integrate APIs and real-time services, drive front-end architecture, optimize performance and accessibility, and contribute to testing and continuous improvement.

Lead technical discovery and early development of an action-recognition CV product for retail: design experiments, build end-to-end video ML pipelines, set up annotation workflows, prototype and evaluate models, optimize precision/recall and latency, and provide technical leadership across product and engineering.

Own end-to-end delivery of specific ADAS features (e.g., TFL, High Beam Assist, Blind Spot Monitoring). Define feature scope, set performance targets, align OEM requirements with internal roadmaps, collaborate with engineering/product/OEM teams, participate in testing/validation, and mitigate risks to ensure features meet specs and production readiness.

Own the DACH market launch for Nebuly, generating pipeline through an established enterprise network and managing the full B2B SaaS sales cycle. Target mid-market and enterprise accounts with €100K+ ACV potential, navigate complex stakeholder groups, build business cases, negotiate, and close deals. Represent Nebuly at market events, collaborate with sales engineering and partners, and develop system integrator and advisory relationships. The role requires German and English fluency, strong enterprise relationships, technical sales ability, and experience closing large contracts without inbound or SDR support.

As an AI Operations & Automation Specialist, you will optimize finance and HR operations through automation, AI implementation, and process improvement while ensuring data integrity and supporting various teams in the company.

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.

Build core components of a diagnostic and personalization platform: backend data pipelines, frontends, services for genomic data ingestion, ML model integration, APIs, and cloud infrastructure. Collaborate with product and ML teams, iterate on prototypes and MVPs, and make architectural decisions supporting scalability and reliability.

Define and execute the product roadmap for AI-driven blockchain security monitoring tools. Collaborate with cross-functional teams, analyze market and customer feedback, deliver features on time, and communicate with stakeholders to align expectations and improve product offerings.

Design and build scalable, low-latency backend APIs and product-stream ranking systems using typed languages. Integrate with data platforms and BI, manage large datasets, collaborate with engineers, PMs, and data scientists, and contribute to new features and technical improvements.

Lead the Affordability domain for Quick Commerce: define vision and roadmap, deliver item-level promotions and pricing solutions, align global stakeholders, partner with engineering and data science, run experiments, and measure impact on conversion, AOV, and retention.

Design and implement algorithms and probabilistic models for array and NGS genotyping. Develop production-grade bioinformatics software and scalable workflows, apply statistical and machine learning methods to large genomic datasets, and maintain testing automation, CI/CD, observability, and software lifecycle practices. Collaborate with wet‑lab scientists and engineers; provide mentorship at staff level.