Intrinsic
Senior Research Scientist, Robotic Foundation Models(m/w/x)
Vollzeitnur vor OrtSenior
München
Neuer Job?Nejo!
Dein persönlicher KI-Karriere-Agent
INIntrinsic
Senior Software Engineer, ML Ops & Infrastructure(m/w/x)
München
VollzeitVor OrtSenior
AI/ML
Nejo KI-Zusammenfassung
Optimizing data pipelines for 1000+ GPU deep learning jobs in industrial robotics. 2 years MLOps or ML infrastructure experience with Python/C++ and Docker/Kubernetes required. Open-source model development and community engagement.
Anforderungen
- Bachelor's degree in Computer Science, Robotics, Machine Learning, or related field
- 2 years of experience in software development with focus on MLOps or machine learning infrastructure
- Proficiency in programming with Python and C++
- Experience with containerization and orchestration technologies, specifically Docker and Kubernetes
- Experience with deep learning frameworks such as TensorFlow, JAX, or PyTorch
- Experience with cloud computing platforms like Google Cloud Platform
- Basic Front-end experience
- Master’s degree or PhD in Computer Science, Robotics, or related field
- Comprehensive knowledge of the entire image processing workflow
- Experience with MLOps toolkits such as Kubeflow
- Hands on experience with CUDA optimization or deep learning optimization
- Experience deploying machine learning models at scale in production environments
- Familiarity with robotics systems or industrial automation hardware
- Practical experience debugging distributed systems and optimizing network performance
- Experience with accelerator orchestration (e.g., XManager)
Aufgaben
- Design and implement scalable infrastructure for deep learning models
- Optimize data loading and training speed for over 1000 GPU jobs
- Build data pipelines for distributed computing of robotics data
- Develop APIs and tools for integrating machine learning techniques
- Lead efforts to open source models and engage with the community
- Optimize compute resource allocation to reduce costs and latency
- Create orchestration workflows for running jobs on GKE
- Develop tools for model understanding and analysis
Berufserfahrung
- 2 Jahre
Ausbildung
- Bachelor-AbschlussODER
- Master-Abschluss
Sprachen
- Englisch – verhandlungssicher
Tools & Technologien
- Python
- C++
- Docker
- Kubernetes
- TensorFlow
- JAX
- PyTorch
- Google Cloud Platform
- Kubeflow
- CUDA
- XManager
Die Originalanzeige dieses Stellenangebotes in der aktuellsten Version findest du hier. Nejo hat diesen Job automatisch von der Website des Unternehmens Intrinsic erfasst und die Informationen auf Nejo mit Hilfe von KI für dich aufbereitet. Trotz sorgfältiger Analyse können einzelne Informationen unvollständig oder ungenau sein. Bitte prüfe immer alle Angaben in der Originalanzeige! Inhalte und Urheberrechte der Originalanzeige liegen beim ausschreibenden Unternehmen.
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INIntrinsic
Senior Software Engineer, ML Ops & Infrastructure(m/w/x)
München
VollzeitVor OrtSenior
AI/ML
Nejo KI-Zusammenfassung
Optimizing data pipelines for 1000+ GPU deep learning jobs in industrial robotics. 2 years MLOps or ML infrastructure experience with Python/C++ and Docker/Kubernetes required. Open-source model development and community engagement.
Anforderungen
- Bachelor's degree in Computer Science, Robotics, Machine Learning, or related field
- 2 years of experience in software development with focus on MLOps or machine learning infrastructure
- Proficiency in programming with Python and C++
- Experience with containerization and orchestration technologies, specifically Docker and Kubernetes
- Experience with deep learning frameworks such as TensorFlow, JAX, or PyTorch
- Experience with cloud computing platforms like Google Cloud Platform
- Basic Front-end experience
- Master’s degree or PhD in Computer Science, Robotics, or related field
- Comprehensive knowledge of the entire image processing workflow
- Experience with MLOps toolkits such as Kubeflow
- Hands on experience with CUDA optimization or deep learning optimization
- Experience deploying machine learning models at scale in production environments
- Familiarity with robotics systems or industrial automation hardware
- Practical experience debugging distributed systems and optimizing network performance
- Experience with accelerator orchestration (e.g., XManager)
Aufgaben
- Design and implement scalable infrastructure for deep learning models
- Optimize data loading and training speed for over 1000 GPU jobs
- Build data pipelines for distributed computing of robotics data
- Develop APIs and tools for integrating machine learning techniques
- Lead efforts to open source models and engage with the community
- Optimize compute resource allocation to reduce costs and latency
- Create orchestration workflows for running jobs on GKE
- Develop tools for model understanding and analysis
Berufserfahrung
- 2 Jahre
Ausbildung
- Bachelor-AbschlussODER
- Master-Abschluss
Sprachen
- Englisch – verhandlungssicher
Tools & Technologien
- Python
- C++
- Docker
- Kubernetes
- TensorFlow
- JAX
- PyTorch
- Google Cloud Platform
- Kubeflow
- CUDA
- XManager
Die Originalanzeige dieses Stellenangebotes in der aktuellsten Version findest du hier. Nejo hat diesen Job automatisch von der Website des Unternehmens Intrinsic erfasst und die Informationen auf Nejo mit Hilfe von KI für dich aufbereitet. Trotz sorgfältiger Analyse können einzelne Informationen unvollständig oder ungenau sein. Bitte prüfe immer alle Angaben in der Originalanzeige! Inhalte und Urheberrechte der Originalanzeige liegen beim ausschreibenden Unternehmen.
Gefällt dir diese Stelle?
BetaDein Career Agent findet täglich ähnliche Jobs für dich.
Über das Unternehmen
Intrinsic
Branche
Other
Beschreibung
The company aims to reimagine the potential of industrial robotics, making it intelligent and accessible for businesses and developers.
Noch nicht perfekt?
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Vollzeitnur vor OrtSeniorMünchen