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Senior Software Engineer, ML Ops & Infrastructure(m/w/x)
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
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- IntrinsicVollzeitnur vor OrtSeniorMünchen
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Senior Software Engineer, ML Ops & Infrastructure(m/w/x)
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
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.
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