Artificial Intelligence Experts in Berlin
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Meet FRATCH Experts in Berlin, who have recently used Artificial Intelligence
Silvia Bürmann
Last position:
Fractional VP Sales, Executive Sales Coach & GTM Advisor, AI Transformation Management at Self-employed
- Advise B2B technology and mid-market companies on commercial strategy, sales effectiveness, operating model design, and scalable growth.
- Coach senior sales leaders and executive teams on GTM choices, leadership effectiveness, accountability, and execution.
- Support market entry and growth planning through structured assessment of customer segments, value propositions, channel options, coverage models, investment priorities, KPIs, and risks.
- Facilitate peer-level strategy sparring and translate strategic decisions into measurable commercial initiatives.
- Combine systemic coaching, sales leadership experience, and change management practice to ensure decisions are practical and adopted.
Chris Wolf
Last position:
Senior Strategy Advisor, Transformation Lead – program realignment with target picture, governance, and priority steering at Sparkassen-Finanzgruppe | S-Communication Services
In-house consulting provider and driver of transformation within the group, multi-stakeholder environment and C-level.
Realignment and stabilization of a cross-functional transformation and scaling program within the group. Sharpening the target picture, priorities, and set of measures, as well as building reliable governance, planning, and steering structures. Structuring roles, responsibilities, and strategic initiatives while including AI and IT automation ideas.
Designed program realignment and project portfolio management
Developed strategy model and target picture for IT projects
Structured portfolio, roadmap, and priorities
Established governance and regular meetings
Worked out operating model for flagship projects
Assessed AI and automation ideas
Clarified roles and responsibilities
Implemented change measures
Developed, moderated, and evaluated workshops
Transformed 17 initiatives into a steering model
Increased transparency and decision-making ability
Strengthened commitment in steering
Sharpened the operating model structurally
Integrated three top-5 institutes
Involved over 80% of stakeholders
Governance
Portfolio steering (PPM)
Change management
Artificial intelligence
Workflow automation
AI use case assessment
Confluence
Jira
Stakeholder management
Dmitry Pankov
Last position:
Freelance Digital Marketing Analyst at Freelance
- Marketing Strategy: Lead the end-to-end analysis and evaluation of cross-channel marketing campaigns across the entire Customer Journey. My focus is identifying optimization potential and deriving clear, actionable recommendations that drive measurable business impact.
- Data Science & AI: Advanced predictive modeling (Churn, LTV), market basket analysis, clustering, and real-time AI-powered audience discovery utilizing RAG/LLMs.
- Marketing Analytics & Measurement: End-to-end attribution analysis, Marketing Mix Modeling (MMM), audience segmentation, conversion path analysis, and A/B testing across all major platforms.
- Data Engineering & Reporting: Designing and managing robust, multi-platform data pipelines (BigQuery, GCP) for data consolidation, automated dashboard generation, and critical API integrations.
Gilad Gotesman
Last position:
European Strategy Atlas – Independent Analytics & Decision-Support Project at Independent Project
Designed and built an end-to-end interactive decision-support application using public European data across 27 EU countries and multiple strategic dimensions. Developed a structured analytical methodology for comparing countries, identifying patterns and trade-offs, and exploring strategic choices rather than presenting static dashboards. Translated complex multidimensional data into guided interactive exploration and learning workflows for non-specialist users. Built the application end-to-end using Python and Streamlit, with AI-assisted development and Git-based version control. Developed the project independently from problem framing and data analysis through methodology, UX logic, implementation and deployment.
Tools: Python, Streamlit, Git, AI-assisted development
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Chintan Padaliya
Last position:
Product Owner and Technical Product Lead at Sustamize GmbH
LLM-based features for automated COâ‚‚e data extraction from unstructured documents (70% reduction)
Agentic AI pipeline for automated Scope 3 emissions calculation with 150,000+ validated data records
Smart API workflows for real-time carbon footprint calculations in ERP and ESG systems
ML algorithms to predict emission hotspots and optimize product design
Automated data validation pipelines with NLP for quality assurance of COâ‚‚e datasets
Led a 15-person cross-functional team to develop 10+ AI features
Strategic product planning and AI roadmap with 35% shorter time to market
Stakeholder management with DAX companies (40% higher satisfaction, 95% retention)
On-time project delivery with 95% budget adherence through data-driven backlog management
Agile methods (Scrum, Kanban) with continuous AI/ML integration (25% team velocity increase)
Product-market fit for AI features through A/B testing and analytics (60% higher adoption rate)
Anjana Rakesh
Last position:
Senior Product Designer at Casavi GmbH
I served as the Lead Designer for two cross-functional teams at Casavi, a software platform for property managers. Casavi is a central platform for all aspects of digital property management, which streamlines operations and business processes.
SmartTask: The team focuses on ticket management, workflow automation, AI integration, enhancing communication between property managers and their clients.
Customer app/portal: The team is dedicated to fostering community engagement among residents of managed properties. The customer portal in combination with the Casavi app solves the challenges for property and facility managers.
My role spans the full design lifecycle, covering UX/UI design, user research, usability testing, and strategic design planning, across Casavi's web platform, mobile app, and customer portals. Each team comprises around 10 members, including a project manager, designer, developers, and QA testers. I am also responsible for the accessibility assurance of the whole product.
Design unit role: In addition to my core responsibilities, I actively contribute to the development and maintenance of the company's design system and style guide ensuring consistency and scalability across all products. Mentor junior designers is my official and moral responsibility.
Patrick Hohensee
Last position:
Lead Technical Recruiter | Business Partner AWS EMEA at Amazon Web Services (AWS)
- Partnered with senior stakeholders across AWS EMEA to drive talent strategy, partner development, and business growth in the cloud ecosystem.
- Focus areas:
- Collaboration with Sales & Partner Management on Go-to-Market initiatives
- Advisory on long-term resource strategy for Cloud, Data, and Security Divisions
- Supporting internal innovation teams in scaling AI and automation projects
- Result: Contributed to AWS’s expansion in Central Europe by aligning business, technology, and people strategy.
Anish Gupta
Last position:
GTM Intelligence Engine · Open Source
- PROBLEM: GTM effort is guesswork across fragmented identities and channels, with no closed feedback loop.
- BUILT: Cost-pyramid engine (L0–L3): identity resolution across ~25k entities, explainable intent scoring, and a closed decision loop (propose → execute → evaluate → learn) with calibration.
- IMPACT: Shipped v1.3.1 with a live demo; 99% of operations resolve at the free L0 tier (CI-enforced); $0 to run without any API key.
Myrto Papagiannakou
Last position:
UX Lead, Strategist for Property Management Systems at Destination Solutions
- Leading UX for a Property Management System, an all-in-one solution for vacation rental agencies and tourism regions, covering marketing and rental of holiday apartments and houses
- UX audits, conception, and implementation of UX strategy with a focus on regulatory, security, and user-centered requirements
- Advising C-level stakeholders on UX strategy and design best practices
- Planning and conducting research with agencies and property owners
- Design system strategy and definition of UX architecture
Piet Quade
Last position:
IT Project Manager at no release
Industry: Publishing, media Project management for the concept of a RAG-based archive access solution: a secure on-prem or hybrid compute architecture for LLM and embedding operations, pipeline for transcription and automatic tagging, semantic search across audio and video archives. Use case evaluation and make-or-buy together with editorial team, archive, and legal department, taking into account copyright, broadcasting law, and the AI Act. Differentiator: practical LLM infrastructure experience from two own productive platforms combined with C-level program management in regulated industries.
Ankit Handa
Last position:
AI Evaluation Analyst at Turing
Driving AI model quality at scale — evaluating prompt-response accuracy, flagging edge cases, and maintaining SLA-compliant workflows across distributed global teams.
- Analyse AI prompts and side-by-side model outputs to assess response quality, factual accuracy, relevance, consistency, and compliance with project evaluation guidelines.
- Perform fact-checking, data validation, troubleshooting, issue identification, and edge-case review to improve quality standards across AI training support workflows.
- Use Google Sheets, Google Docs, and browser-based tools to document findings, maintain evaluation logs, track issue patterns, and support workflow optimisation in a remote environment.
- Create clear written justifications, review summaries, and KPI-oriented reporting focused on accuracy, turnaround time, documentation completeness, defect identification rate, and SLA adherence.
Dave Mooney
Last position:
Founder & Lead Designer at Dave Mooney Software
- Leading end-to-end UX for two AI SaaS products in closed beta, including LLM-interaction design, prompt-UX, and human-in-the-loop patterns with commercial distribution signed for launch in Q3 2026
- Built a self-built LLM reframing and RAG-correction pipeline powering multi-profile CV and case-study generation in production use
- Shipping real code alongside research, including Three.js/GLSL portfolio work, Figma-API tooling, and a Chrome MV3 extension for session-sync automation
Rashi Jain
Last position:
Design Consultant at Valutics Inc.
- Designing UX for a B2B AI SaaS platform covering the full software development lifecycle, including an orchestration transparency panel showing users which AI model is active at each stage, reducing AI opacity and building user trust in multi-model workflows.
Mirjam Walser
Last position:
AI Trainer / Data Annotator at DataAnnotation, Outlier
- Review and creation of German-language training data for AI models, with a focus on language quality, tone of voice, and suitability for target groups.
- Design of prompts and evaluation frameworks for quality assurance of AI responses.
- Prompt design and creation of AI training content in German and English.
- Language and voice training for AI models in German.
Alexander Zhirov
Last position:
Senior Data Solutions Engineer at VMware Inc.
- Architected and deployed private cloud data platform on VMware vSphere, integrating Greenplum MPP, Apache Kafka, Kubernetes, and Apache Solr, and developed real-time ingestion pipelines with Kafka Connect and Schema Registry.
- Led Oracle Exadata to Greenplum migration, rearchitected data models, optimized storage, implemented RabbitMQ with Debezium for CDC, and deployed VectorDB for Generative AI.
- Designed and executed multi-cloud migration PoC across AWS, Azure, and GCP, defined KPIs for throughput, latency, and cost efficiency, executed bulk data transfers, validated analytics and streaming workloads, and delivered full-scale architecture recommendations.
- Assessed legacy on-premises infrastructure and designed modern cloud-native data platforms using Greenplum and containerized microservices, advising on scalability, disaster recovery, and high-availability.
Discover over 15,000 top freelancers
Statistics of experts using Artificial Intelligence
Aggregated from the professional profiles of matched freelancers.
Experience
16 years (Germany: 18 years)
Position duration
2.5 years (Germany: 3.1 years)
Positions per freelancer
9 (Germany: 10)
Top business areas
Product Development, Information Technology, Project Management
Top industries
Information Technology, Professional Services, Education
Certification focus areas
Information Technology, Product Development, Project Management
Bachelor's degree or higher
97% (Germany: 92%)
Master's degree or higher
64%
Doctorate
9% (Germany: 11%)
Certifications per freelancer
2 (Germany: 3)
Most common languages
English, German, French
Speak two or more languages
95% (Germany: 97%)
Based on our profile pool as of 30 Aug 2026.
Daily rate distribution
The chart shows how the daily rates of freelancers in this technology in Berlin are distributed, based on recent contracts on our platform. Each bar covers a rate range — its height shows how many freelancers charge within that range.
Average rates of experts in Berlin using Artificial Intelligence
Rates are based on recent contracts and do not include FRATCH margin.
The average daily rate is the mean of all daily rates from recent contracts of comparable freelancers on our platform.
The median daily rate is the middle value of all daily rates — half of comparable freelancers charge less, half charge more. Unlike the average, it is barely affected by outliers.
Calculated based on our freelancers’ daily rates as of 30 Aug 2026. Actual rates may vary depending on seniority level, experience, skill specialization, project complexity, and engagement length.
About the technology
What AI covers
Artificial Intelligence is used to build systems that classify data, generate text and images, detect patterns, and support decisions. In product teams it often sits inside search, support automation, forecasting, document workflows, and recommendation features.
Common stack
- Python, PyTorch, TensorFlow, scikit-learn
- LLM tools, prompt design, embeddings, vector search
- Data pipelines, feature stores, evaluation and monitoring
- Cloud services, APIs, and deployment tooling
Strong specialists know how to connect models to real business data, not just run notebooks. They understand data quality, latency, retrieval, and how to keep outputs useful after launch.
When teams hire
Companies bring in freelance AI experts when a use case is clear but the internal team lacks depth. That includes proof-of-concept work, model comparison, RAG setups, fine-tuning, or cleanup after a stalled build.
- A product needs AI features but no clear technical path
- An existing model needs better quality or lower cost
- Data, prompts, or evaluation are weak
- A launch needs temporary specialist support
What strong experts do
Good Artificial Intelligence specialists turn business goals into measurable tasks. They define data needs, choose the right approach, test outputs against real cases, and document limits so teams can use the system safely.
They also know when a simpler rule-based solution is better than a model. That judgement matters in Berlin teams working across startups, media, industry, and enterprise software.
Ecosystem and skills
The AI ecosystem often includes large language models, retrieval-augmented generation, vector databases, MLOps, and cloud deployment. Depending on the project, specialists may work with OpenAI, Anthropic, Hugging Face, LangChain, or custom model stacks.
A solid expert can move between data prep, experimentation, evaluation, and production handoff. They write clear documentation and keep the system maintainable for the in-house team.
Hiring in Berlin
Berlin companies often need AI specialists who can work with product, data, and engineering teams in English, and sometimes in German. Remote delivery is common, but on-site workshops help when access to sensitive data or cross-team alignment is important.
For local hiring, look for people who can explain model choices clearly, handle changing requirements, and deliver concrete outputs rather than vague experiments.
Frequently asked questions
Not sure where to start with Artificial Intelligence? These answers cover the essentials.
A strong Artificial Intelligence specialist delivers working outcomes such as model prototypes, prompt flows, retrieval setups, evaluation methods, or production-ready integrations. The focus should be on a clear use case, useful output, and a path to maintain the system after handover.
AI is the broader term. Machine learning is one major part of it, while modern projects may also include rule systems, search, language models, and computer vision. When you hire, it helps to know whether you need a general AI specialist or someone focused on ML, LLMs, or applied analytics.
Artificial Intelligence projects that handle text, assistants, or document workflows often benefit from LLMs, retrieval, and prompt design. If the task is prediction, classification, or forecasting from structured data, classic machine learning can be the better fit. A good specialist will compare both paths before building.
A capable Artificial Intelligence freelancer usually brings strong Python skills, data handling, evaluation methods, and cloud or API integration. For product work, experience with UX for AI features, logging, monitoring, and privacy-aware data handling is also valuable.
You do not need a full spec, but you should have a clear problem, target users, and sample data or example cases. AI work moves faster when the expert can test ideas against real input instead of guessing requirements. Even a short discovery phase can save a lot of rework.
Yes, Artificial Intelligence work is often handled remotely, especially for design, model work, and integration tasks. Berlin teams sometimes prefer in-person sessions at the start for access, stakeholder alignment, or data review. A mixed setup is common when the project touches sensitive systems.
Look for clear examples of shipped work, a practical evaluation approach, and the ability to explain trade-offs in plain language. A good AI expert should talk about data quality, failure cases, latency, and maintenance, not only model names. If they can define success metrics for your use case, that is a strong sign.
Artificial Intelligence is the wider field. Generative AI is the part that creates text, images, code, or other content, often using large language models. If your project needs automation, classification, or decision support, you may need broader AI skills, not only generative tools.
The average hourly rate of freelancers in Berlin, Germany who have used Artificial Intelligence in their recent projects is 104 €, which corresponds to a daily rate of about 833 € based on an 8-hour working day.
Of the freelancers in Berlin, Germany who have used Artificial Intelligence in their recent projects, 97% hold at least a Bachelor's degree, 64% hold at least a Master's degree, and 9% hold a doctorate.
On average, freelancers in Berlin, Germany who have used Artificial Intelligence in their recent projects have 16 years of professional experience, with a single engagement typically lasting around 2.5 years.
The most common languages among freelancers in Berlin, Germany who have used Artificial Intelligence in their recent projects are English (98%), German (94%), and French (18%).
The most common industries among freelancers in Berlin, Germany who have used Artificial Intelligence in their recent projects are Information Technology (85%), Professional Services (52%), and Education (40%).
The most common business areas among freelancers in Berlin, Germany who have used Artificial Intelligence in their recent projects are Product Development (79%), Information Technology (78%), and Project Management (60%).
Main locations of FRATCH Experts, who have recently used Artificial Intelligence
Our freelancers and interim experts are at home across the DACH region — available on-site in the major business hubs or fully remote. Choose a location to discover matched specialists, local market insights and up-to-date availability.
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