20 beste Stellen als lead machine learning engineer in münchen – aktuell auf Personalsuche

AI Innovation Engineer, Google Cloud
Google —München
- 150.000 € – 154.000 € pro Jahr
- Vollzeit
- Informatik
- DevOps
- Java
4 Std.
Computational Engineer
Proxima Fusion —München
- Vollzeit
- CAD
- Mechanikkenntnisse
- Python
Plasma Spectroscopy Diagnostician
Proxima Fusion —München
- Vollzeit
- Master
- Ohne Hochschulabschluss
- Softwareentwicklung
6 Tage
Head of Data Science
Flexa —München
- 140.000 € – 200.000 € pro Jahr
- Vollzeit
- Informatik
- Master
- Machine Learning
Direkt bewerben
Applied AI, Technical Lead, Forward Deployed AI Engineer
Mistral AI —München
- Vollzeit
- Azure
- Doktorat
- Informatik
1 Tag
Computational Physicist
Proxima Fusion —München
- Vollzeit
- Doktorat
- Master
- C++
Consulting Manager (m/f/d) Data & AI Strategy
Artefact —München
- Vollzeit
- Informatik
- Master
- Bachelor
Mechanical Design Engineer
Proxima Fusion —München
- Vollzeit
- Hybrides Arbeiten
- CAD
- Produktion
- Mechanikkenntnisse
Lab Technician
Proxima Fusion —München
- Vollzeit
- Englisch
- Montage
Senior Data & AI Consultant/Consulting Lead (Germany)
Unit8 SA —München
- Vollzeit
- Hybrides Arbeiten
- Informatik
- Master
- Bachelor
- Homeoffice-Möglichkeit
- Flexible Arbeitszeiten
Direkt bewerben
Senior Systems Software Engineer
Terra Quantum —München
- C++
- APIs
- Führungserfahrung
Staff Data Scientist - Trading (d/f/m)
Entrix —München
- 115.000 € – 135.000 € pro Jahr
- Vollzeit
- Informatik
- AWS
- Machine Learning
Direkt bewerben
Technical Account Manager - Commercial Vehicles (m/f/d)
MathWorks —München
- Bachelor
- Ohne Hochschulabschluss
- Mit Reiseanteil
Solution Engineer
Mercura —München
- Vollzeit
- Vertrieb
- Unternehmensentwicklung
- APIs
- Aufstiegsmöglichkeiten
Direkt bewerben
Technical Lead - AI Manipulation and Simulation (Mensch)
Neura Robotics —München
- Vollzeit
- Informatik
- C++
- Machine Learning
Direkt bewerben
Forward Deployed Engineer - EMEA
Tulip Interfaces —München
- Projektmanagement
- Ohne Hochschulabschluss
- Mit Reiseanteil
- Kostenbeteiligung am Arbeitsweg
- Flexible Arbeitszeiten
Direkt bewerben
Applications Engineering, Principal Engineer
Synopsys —Ismaning
- Doktorat
- Master
- Projektmanagement
14 Tage
Teamlead AI Engineering - RoboGym (Mensch)
Neura Robotics GmbH —München
- Vollzeit
- Azure
- Informatik
- Englisch
- Mitarbeiter-Rabatt
- Flexible Arbeitszeiten
10 Tage
Electronics Design Engineer
Terra Quantum —München
- Führungserfahrung
- Python
AI & Analytics Advisory Senior Manager – Agentic AI (all genders)
Accenture —München
- Vollzeit
- Azure
- Künstliche Intelligenz

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lead machine learning engineer jobs near münchen

AI Innovation Engineer, Google Cloud

Google -
München

Jetzt bewerben

Details zur Stelle

Vollzeit
150.000 € – 154.000 € pro Jahr
vor 4 Stunden

Qualifikationen

CI/CD
Datenmodellierung
Go
Informatik
DevOps
NoSQL
Java
Datenbanken
Bachelor
Machine Learning
Terraform
Deep learning
Künstliche Intelligenz
Erfahrung im Bankwesen
Python
Design Patterns

Vollständige Stellenbeschreibung

Note: By applying to this position you will have an opportunity to share your preferred working location from the following: Frankfurt am Main, Germany; Munich, Germany; London, UK.

Minimum qualifications:

Bachelor's degree in Computer Science, a related field, or equivalent practical experience.
7 years of experience in software or data engineering, including one or more programming languages (e.g., Python, Go, Java), and with design patterns, testing frameworks, and API contract design.
Experience using machine learning methodologies (deep learning, reinforced learning), model identification, selection and AI operations (e.g., model monitoring).
Experience using Generative AI and agentic orchestration utilizing frameworks (e.g., LangChain, CrewAI, or Vertex AI Agent Builder) and vector databases.

Preferred qualifications:

Experience in financial services, and with the regulatory and operational clearing, settlement, or custody.
Experience with FSI regulatory practices and data residency, encryption at rest/transit (CMEK), and "explainable AI" requirements in banking.
Experience with data modeling of relational, NoSQL, and analytical data modeling (Star Schema, Data Vault, etc.).
Experience in BigQuery, Vertex AI, Dataflow, and Pub/Sub with an ability to drive the discovery phase, moving from a vague business problem to a structured product requirement document (PRD) and a working technical demo.
Experience working in a high-maturity DevOps culture (e.g., trunk-based development, automated testing, blue/green deployments).

About the job

In this role, you will accelerate customer value and increase adoption by delivering innovative, repeatable, and enterprise-ready solutions focused on business value. Make Google Cloud the preferred choice for customers by delivering the highest-value, industry relevant solutions.

Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.

Individual pay is determined by factors including job-related skills, experience, and relevant education or training.

Germany: €150000 - €154000 (EUR) + 20% bonus target + equity + benefits

Learn more about benefits at Google.

Responsibilities

Design and build autonomous agentic workflows utilizing machine learning and generative AI technologies as part of a fully autonomous or human-in-the-loop agentic workflow.
Partner with client leads(business user) to identify high-impact AI use cases. Translate these into product requirement documents (PRDs), clearly defining critical user journeys (CUJs) and success metrics.
Evaluate and integrate AI solutions with modern data foundations, including relational databases, data lake houses, and real-time streaming architectures.
Ensure all prototypes are built with a "production-first" mindset. Implement basic CI/CD pipelines and utilize infrastructure-as-code (IaC) (e.g., Terraform) to ensure environments are reproducible and secure.
Create clear technical guides to ensure a seamless hand-off from POC to engineering teams.

Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form.

Jetzt bewerben

Erweiterte Suche

lead machine learning engineer Jobs in münchen

AI Innovation Engineer, Google Cloud

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Head of Data Science

Applied AI, Technical Lead, Forward Deployed AI Engineer

Computational Physicist

Consulting Manager (m/f/d) Data & AI Strategy

Mechanical Design Engineer

Lab Technician

Senior Data & AI Consultant/Consulting Lead (Germany)

Senior Systems Software Engineer

Staff Data Scientist - Trading (d/f/m)

Technical Account Manager - Commercial Vehicles (m/f/d)

Solution Engineer

Technical Lead - AI Manipulation and Simulation (Mensch)

Forward Deployed Engineer - EMEA

Applications Engineering, Principal Engineer

Teamlead AI Engineering - RoboGym (Mensch)

Electronics Design Engineer

AI & Analytics Advisory Senior Manager – Agentic AI (all genders)

Ich möchte aktuelle Job-E-Mails für Stellen als lead machine learning engineer in münchen erhalten

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