Data Scientist, AI Engineer – Focus on Machine Learning & GenAI

Expert Analytics GmbH

Data Scientist / AI Engineer entwickelt Machine-Learning-, GenAI- und Data-Engineering-Lösungen für Kunden und eigene Produkte. Mitarbeit an „resonyx“, einer KI-Plattform für akustische Zustandsüberwachung und vorausschauende Wartung.

Posted 8/10/2026full-timeMünchen • 🇩🇪 GermanyMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and implementing machine learning models, data pipelines, and AI workflows, with a strong foundation in Python and relevant data science libraries. Capable of leading projects independently while effectively communicating complex technical concepts to diverse stakeholders.

Highest-signal resume keywords

Machine Learning Model DevelopmentData Pipeline DesignPython ProficiencyGen-AI Frameworks ExperienceCloud Architecture Knowledge

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine LearningData ScienceComputer VisionPredictive AnalyticsRAG Pipeline DesignAcoustic Data AnalysisMathematical ModelingSoftware DevelopmentAnomaly DetectionAI Workflow Design

Soft Skills

Proactive Work StyleSolution-Oriented ApproachClear CommunicationOpenness to LearningCollaboration

Tools & Technologies

PythonC++AWSAzureDockerKubernetesLangChainPydantic AIOpen-Source ModelsEdge-Compute Platforms

Industry Keywords

Data ScienceMachine LearningArtificial IntelligenceSTEM FieldTechnical Systems OptimizationCloud ApplicationsProduction EnvironmentsVisualizationsLow-Latency Data CollectionInterdisciplinary Collaboration

Tech Stack

Tools & technologies

AWSAzureCloudDockerKubernetesPython

About the role

Key responsibilities & impact

Lead projects independently and end-to-end, from initial project communication through architecture to final implementation
Drive data-driven innovation in close collaboration with the CTO and the interdisciplinary team
Design and implement RAG (Retrieval-Augmented Generation) pipelines
Integrate GenAI APIs and open-source models into production customer solutions
Design modern AI agent workflows
Develop, train, and deploy ML models end-to-end
Implement computer vision and predictive analytics solutions
Develop custom specialist software, visualizations, edge-compute platforms, and low-latency data collectors
Analyze complex acoustic data for anomaly detection and further develop audio-based AI workflows
Design and build robust data pipelines for cloud, on-premises, and edge applications
Mathematically model, simulate, and optimize technical systems

Requirements

What you’ll need

Completed degree (Master's or PhD) in Computer Science, Data Science, Physics, Mathematics, Mechanical Engineering, or a comparable STEM field
Residence in or near Munich, or willingness to relocate for the position
Relevant practical or professional experience in data science, machine learning, or software engineering
Ambitious graduates are welcome to apply with relevant hands-on projects, open-source contributions, Kaggle projects, or strong industry internships
Strong proficiency in Python
Experience with common data science and ML libraries in production environments
Practical experience with C++, cloud architectures such as AWS or Azure, Gen-AI frameworks like LangChain or Pydantic AI, or containerization with Docker or Kubernetes is a strong plus
Ability to explain complex technical topics clearly and communicate with non-technical colleagues and customers
Proactive, self-directed, and solution-oriented work style
Openness to new tasks and technological challenges and a passion for continuous learning
Very good German language skills
Good English skills are an advantage

Benefits

Comp & perks

Permanent employment (37.5 hours per week)
Flexible working hours
Remote work by arrangement in a hybrid model
Modern office in the heart of Munich as your home base
Opportunity to work on international projects
Work on solutions with tangible value and contribute to in-house products such as "resonyx"
Appreciative environment with flat hierarchies
Collaboration with PhD-level colleagues and senior data scientists on an equal footing
Room for continuous learning
Regular team events
Open knowledge sharing
State-of-the-art hardware of your choice