Machine Learning Experts in Stuttgart
in minutes from 15,000 CVs with the power of AIHire experts who build prediction models, recommendation systems, computer vision workflows and MLOps pipelines with machine learning, ML, TensorFlow, PyTorch and scikit-learn, matched fast and precisely with vetted, available freelancers.
Meet FRATCH Experts in Stuttgart, who have recently used Machine Learning
Karin Albiez
Last position:
AI Benchmark Engineer | Native language specialist German at Lilt
- Task Engineering: Evaluating Coding Agents.
- Asset Creation: Building realistic task environments using datasets and files in German. Crucially, these assets must remain in the target language to genuinely measure multilingual handling.
- Prompting & Translation: finding failure points where AI does not work, in German.
- Implementation & Verification: Supporting the development of robust solutions (reference implementations) and write highly reliable, deterministic verifier scripts (using rubric-based judging only when strictly necessary).
- Calibration & Execution: Analyze execution logs and calibrate task difficulty (Easy to Very Hard) using standard Terminal-Bench run configurations against various model tiers (Haiku, Opus).
- Quality Assurance: Participation in a rigorous, 4-layer human quality control process (creation, human review, calibration review, and audit) alongside automated LLM-based checks to ensure fairness, grammatical accuracy, and benchmark integrity.
- Linguistic Review: Reviewing AI benchmark tasks across Hindi, Arabic, Japanese, Chinese, Czech and Turkish.
Talha Erciyes
Last position:
Interim Senior Finance Business Partner at SharkNinja Europe Ltd.
Responsibility for commercial finance in Central Europe (DACH and Poland), reporting to the EMEA Commercial Finance Director. Monthly financial reporting, forecasting, and variance analysis, evaluation of promotions and special campaigns, management of planning processes including budgeting, as well as preparation of QBR materials up to CFO level. Took over functional leadership in the finance team after the mandate holder was unavailable.
Dennis Dickmann
Last position:
Founder at Latence
- Founded Latence to commercialise runtime safety patterns from HALO as a deployable product.
- Built end-to-end as single technical founder with open-source stack on NVIDIA ecosystem.
- Developed TRACE: real-time safety layer for knowledge agents and RAG pipelines with groundedness scoring, prompt-attack detection, GDPR redaction, context compression, audit-ready traces.
- Developed vLLM Factory: production inference framework on vLLM with custom Triton kernels and 12 parity-validated plugin models, achieving up to 11.7× throughput vs vanilla PyTorch.
- Developed ColSearch: single-node multi-vector late-interaction retrieval engine with Rust SIMD and fused CUDA, achieving 3.12× FastPlaid geomean QPS on BEIR-8 and a 1.58-bit quantized lane 6.4× smaller than FP16.
- Developed llm-opt: LLM compression research framework with hierarchical importance, structured pruning, tabu search, knowledge distillation.
Francis Wambugu
Last position:
German Teacher at Goethe Institut-Nairobi
- Teaching German literature and linguistics
Jochen Mader
Last position:
Technical Project Lead – Software Development at IT Security (Defense) / CyberSecurity
Technical project lead for the software testing subproject in the development of encryption systems (tactical crypto devices).
Test monitoring
Test specification
Software test implementation
Schedule planning
Code reviews
Team leadership
Test team resource planning
Test team coordination
Coordination of overall project flow
Stakeholder management
Report creation
Reporting to executive management
Delivered testing milestones on schedule, ensuring timely integration with development.
Improved test team efficiency by standardizing workflows and reporting.
Ensured compliance with Common Criteria (ISO/IEC 15408).
Meenakumar Vaikundam
Last position:
Senior Embedded Technical Manager at IIT Madras Pravartak Technologies
- Led 14 member dev team and delivered postgresql database integration and performance optimization
- Delivered 8 K lines of C code with fewer defects (5 medium to low) in 8 months of development
- Integrate open source pgVector for AI application of the database for exact and nearest neighbor search
Ivan Greguric-Ortolan
Last position:
Technical Lead at Porsche Digital GmbH
- Contributed to the design of the new financial services integration layer and moderated the architectural discussions
- Oversaw the security concept and approval of the application
- Prepared infrastructure setup and best practices for the Kotlin backend
Friederike Bohm
Last position:
Independent Consultant and Trainer at Friederike Bohm Consulting
- Consulting on lean, logistics, AI applications and process optimization
- Customized concepts for digitalization, change & transformation
- Adaptive training and workshops for professionals and managers
Noushiq Mohammed K A N
Last position:
Projects at Institute for Intelligent Systems
- Evaluation and analysis of camera-based traffic light and sign recognition system on various LLM-based autonomous driving systems (LMDrive, BEVDriver)
- Implemented VLM based traffic notice instruction generation unit for closed-loop autonomous driving system which alerts driver in unforeseen driving incidents
- Developed independent LLM-based local chatbot with Llama, DeepSeek and Qwen including MLflow evaluation framework
Michael Berger
Last position:
Program and Project Manager at Independent
- Project management: rollout, migration and implementation of international IT projects
- Sales and business development
- Finance and team management (up to 24 senior consultants) and stakeholder management (including executive level)
- Projects include diverse SAP ERP; SAP S/4HANA; cloud/on-premise, AI, machine learning
- Responsible for project computerized system validation (CSV), QA, project quality
- Implementation of CSV, QA in the project
- Key account management; responsible for all client projects and offerings
- Development of RFIs and RFPs
Christian Saba
Last position:
Research Associate – AI Consultant at Fraunhofer IAO
- Developed NLP and LLM POCs for use in manufacturing companies
- Applied advanced machine learning algorithms to analyze production data and develop custom data pipelines for quality assurance
- Designed and led the IAO basic seminar on AI in industry, including hands-on training modules
Chaima Dahri
Last position:
Data Scientist Intern at Marelli Automotive Lighting
- Developed and deployed a deep learning model for automated keypoint detection in headlamp light distributions.
- Prepared and processed datasets, and selected VGG16 after benchmarking CNN architectures for the best accuracy efficiency trade-off.
- Delivered a Flask REST API, containerized with Docker, and integrated the solution into an existing internal system, enabling automated and efficient evaluation of headlamp designs.
Stefan Pölz
Last position:
Senior Software Engineer / Software Architect at Freelance
- I am available as a freelance (full-stack) software developer and/or architect to work in agile teams and develop high-quality applications together.
Sakshi Chaudhari
Last position:
Full Stack LLM Developer at Accenture
- Analyzed business needs and collaborated with stakeholders to translate them into technical requirements and user stories, guiding AI solution development within Agile Scrum teams.
- Designed, built, and deployed scalable Large Language Model (LLM) solutions supporting digital transformation initiatives, focusing on client requirements and outcome-driven delivery.
- Implemented Retrieval-Augmented Generation (RAG) pipelines using vector databases to enhance knowledge services that support business decision-making.
- Collaborated closely with cross-functional teams, including data scientists, product managers, and business analysts, to ensure AI solutions aligned with business goals.
- Provided end-to-end client support, ensuring smooth adoption and resolving operational issues in production deployments.
- Engaged in continuous learning and training to enhance consulting skills and agile project management.
- Planned and created test cases, executing manual and automated testing using Selenium and Jira for enterprise applications.
- Documented test results and collaborated with development teams to ensure high-quality software delivery.
Dean Rakic
Last position:
CEO / Chief Scientist at ENUM
- Blockchain platform technology
- Blockchain digital platform / Digital Economy.
Discover over 15,000 top freelancers
Statistics of experts using Machine Learning
Aggregated from the professional profiles of matched freelancers.
Experience
14 years
Position duration
2.3 years (Germany: 2.8 years)
Positions per freelancer
7 (Germany: 8)
Top business areas
Product Development, Information Technology, Research and Development
Top industries
Automotive, Information Technology, Manufacturing
Certification focus areas
Information Technology, Project Management, Business Intelligence
Bachelor's degree or higher
100% (Germany: 97%)
Master's degree or higher
77%
Doctorate
23% (Germany: 19%)
Certifications per freelancer
2
Most common languages
German, English, French
Speak two or more languages
95% (Germany: 98%)
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 Stuttgart 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 Stuttgart using Machine Learning
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 it covers
Machine learning turns data into models that predict, classify and recommend. It is used for demand forecasting, anomaly detection, document processing and product personalization. Strong professionals connect the method to a real business goal, not just a notebook experiment.
Common stacks
- Python, scikit-learn, TensorFlow and PyTorch
- Feature engineering, model evaluation and tuning
- Batch scoring, APIs and automated retraining
- Cloud data pipelines and MLOps tooling
These tools support both fast prototypes and production systems.
Where it fits
Companies bring in freelance expertise when they need a model built, improved or moved into production. The work often sits inside analytics, data products, search, fraud checks or industrial systems. In Stuttgart, this can also support manufacturing, mobility, engineering and enterprise software teams.
Strong profiles
Good specialists work cleanly across data, model and deployment steps. They document assumptions, handle leakage and bias checks, and explain trade-offs in plain language. They also know when a simple model is better than a complex one.
Typical projects
- Building supervised and unsupervised models
- Training classifiers, rankers and forecasting models
- Setting up monitoring and retraining loops
- Integrating models into apps, APIs or dashboards
These deliverables matter when a company wants usable output, not just experiments.
Collaboration style
Many machine learning experts work remotely, especially for model development and review. On-site collaboration in Stuttgart is useful when access to internal data, teams or domain experts matters. Clear requirements, data access and success criteria make the work much smoother.
Frequently asked questions
The facts hiring teams ask for most often when it comes to Machine Learning.
Machine Learning is used to turn historical data into predictions or decisions. Companies use it for forecasting, classification, anomaly detection, recommendation and automation. It is a fit when rules alone are too rigid and the data keeps changing.
ML is a part of AI, but not the whole thing. AI is the broader field; machine learning is the method that lets systems learn patterns from data. In hiring, people often say AI when they really need an ML specialist.
Machine Learning is better when patterns are complex and data-driven decisions matter. Rule-based systems are easier to explain, but they struggle when conditions change often. Statistics and ML overlap, yet ML usually focuses more on prediction at scale and operational use.
A strong machine learning specialist usually knows Python, data preparation, model validation and deployment basics. Useful adjacent skills include SQL, cloud services, experiment design and MLOps. Domain knowledge also matters because the model must solve the right problem.
Projects with messy data, unclear targets or production needs usually need senior help. Machine Learning work becomes harder when models must be monitored, retrained and explained to other teams. If the outcome affects revenue, risk or operations, a more experienced specialist is usually the safer choice.
Yes, much of Machine Learning can be done remotely because data access, model building and review happen digitally. On-site work in Stuttgart helps when the specialist needs close contact with business experts, sensitive data or operational teams. Many projects use a hybrid setup.
For ML, check whether the specialist has shipped models into real use, not only trained them in notebooks. Ask about data quality handling, validation methods, deployment experience and how they measure model drift. Clear examples of past work are a good sign.
Machine Learning work often uses scikit-learn for classic models and fast baselines. TensorFlow and PyTorch are more common for deep learning and complex neural networks. The right choice depends on the data, the task and how the model will be maintained.
The average hourly rate of freelancers in Stuttgart, Germany who have used Machine Learning in their recent projects is 78 €, which corresponds to a daily rate of about 621 € based on an 8-hour working day.
Of the freelancers in Stuttgart, Germany who have used Machine Learning in their recent projects, 100% hold at least a Bachelor's degree, 77% hold at least a Master's degree, and 23% hold a doctorate.
On average, freelancers in Stuttgart, Germany who have used Machine Learning in their recent projects have 14 years of professional experience, with a single engagement typically lasting around 2.3 years.
The most common languages among freelancers in Stuttgart, Germany who have used Machine Learning in their recent projects are German (100%), English (95%), and French (32%).
The most common industries among freelancers in Stuttgart, Germany who have used Machine Learning in their recent projects are Automotive (64%), Information Technology (59%), and Manufacturing (50%).
The most common business areas among freelancers in Stuttgart, Germany who have used Machine Learning in their recent projects are Product Development (86%), Information Technology (82%), and Research and Development (73%).
Main locations of FRATCH Experts, who have recently used Machine Learning
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.
Berlin 
Hamburg 
Munich 
Cologne 
Frankfurt 
Dusseldorf 
Dortmund 
Essen 
Bremen 
Dresden 
Hanover 
Nuremberg Request a free demo
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Philipp Thomaschewski
FRATCH CEO
