- As a Research Engineer you will develop cutting-edge Vision-Language-Action (VLA) architectures that empower AI agents to interpret human instructions and act autonomously in complex environments.
- Furthermore you will connect multimodal representation learning with long-term control and planning to create agents that go beyond reactive capabilities and exhibit cognitive intelligence.
- You will contribute to fundamental and applied research on novel VLA models and actively drive their advancement.
- Building a scalable infrastructure for experimentation training and deployment including the development of training pipelines simulation tools and evaluation methods will be part of your task.
- You will make VLA methods usable for concrete Bosch applications in practice and demonstrate their superior flexibility and generalization capabilities.
- Last but not least you will work closely with interdisciplinary teams of researchers and application experts to shape the early innovation phase and the long-term strategy for intelligent automation at Bosch.
Qualifications :
- Education:
- excellent MSc in Computer Science Machine Learning Robotics or related technical fields
- PhD in Multimodal AI Robotics Reinforcement Learning or Generative AI preferred
- demonstrated academic excellence with a strong publication record in leading AI and robotics conferences and journals (NeurIPS ICLR ICML CVPR CoRL RSS ICRA ACL EMNLP etc.)
- Experience and Knowledge:
- Industrial SW development experience:
- Demonstrated industry-relevant practical AI experience e.g. by code contributions in industrial AI applications in large scale machine learning projects or participation in large-scale AI benchmarks and contests
- Multiple years of experience in developing and deploying machine learning solutions in distributed SW development teams
- Demonstrated capability to go beyond research prototypes and integrate cutting-edge AI methods into practically relevant and usable SW solutions
- Multimodal AI & Vision-Language Models:
- Proficiency in designing and training vision-language models (VLMs) and language-multimodal models (LMMs) (e.g. Flamingo GPT-4V PaLM-E RT-2)
- Hands-on experience with visual grounding cross-modal attention and instruction-following architectures
- Familiarity with benchmarks such as ALFRED Ego4D VLN or datasets involving perception and action
- Control Reinforcement Learning & Planning:
- Strong experience in reinforcement learning imitation learning or model-based control for agents operating in real or simulated environments
- Capability in designing agents for long-horizon planning semantic task decomposition and hierarchical control
- Knowledge of methods that combine perception language and action in task-driven settings
- AI for Cyber-Physical Systems & Automation:
- Demonstrated capability to integrate cutting-edge AI methods into practical applications in robotics automated
- driving industrial automation or building systems interest in emerging domains such as smart heating and HVAC control where semantic AI can optimize control strategies
- Focus on building robust explainable and semantically grounded agents for physical deployment
- Infrastructure Simulation & Tooling:
- Proficient in Python and deep learning libraries such as PyTorch TensorFlow or JAX
- Experience with simulation platforms such as Isaac Sim CARLA MuJoCo or Habitat
- Skilled in developing scalable pipelines using Docker CI/CD and multi-GPU/cloud infrastructure
- Proven ability to drive research projects and turning research into practical innovation
- Collaborative and interdisciplinary mindset able to work across research and product teams at Bosch
- Personality and Working Practice: you have proven ability to drive research projects and turning research into practical innovation; collaborative and interdisciplinary mindset you are able to work across research and product teams at Bosch
- Languages: fluent English German is optional
Additional Information :
submit all relevant documents (CV certificates and links to GitHub or kaggle account).
We offer flexible working models: from various part-time options to mobile working and job sharing. Feel free to contact us.
Diversity and inclusion are not just trends for us but are firmly anchored in our corporate culture. Therefore we welcome all applications regardless of gender age disability religion ethnic origin or sexual identity.
Need support during your application
Meltem Arabacioglu (Human Resources)
Need further information about the job
Jim Mainprice (Functional Department)
49 9
Michael Pfeiffer (Functional Department)
49 5
Remote Work :
No
Employment Type :
Full-time
As a Research Engineer you will develop cutting-edge Vision-Language-Action (VLA) architectures that empower AI agents to interpret human instructions and act autonomously in complex environments.Furthermore you will connect multimodal representation learning with long-term control and planning to c...
- As a Research Engineer you will develop cutting-edge Vision-Language-Action (VLA) architectures that empower AI agents to interpret human instructions and act autonomously in complex environments.
- Furthermore you will connect multimodal representation learning with long-term control and planning to create agents that go beyond reactive capabilities and exhibit cognitive intelligence.
- You will contribute to fundamental and applied research on novel VLA models and actively drive their advancement.
- Building a scalable infrastructure for experimentation training and deployment including the development of training pipelines simulation tools and evaluation methods will be part of your task.
- You will make VLA methods usable for concrete Bosch applications in practice and demonstrate their superior flexibility and generalization capabilities.
- Last but not least you will work closely with interdisciplinary teams of researchers and application experts to shape the early innovation phase and the long-term strategy for intelligent automation at Bosch.
Qualifications :
- Education:
- excellent MSc in Computer Science Machine Learning Robotics or related technical fields
- PhD in Multimodal AI Robotics Reinforcement Learning or Generative AI preferred
- demonstrated academic excellence with a strong publication record in leading AI and robotics conferences and journals (NeurIPS ICLR ICML CVPR CoRL RSS ICRA ACL EMNLP etc.)
- Experience and Knowledge:
- Industrial SW development experience:
- Demonstrated industry-relevant practical AI experience e.g. by code contributions in industrial AI applications in large scale machine learning projects or participation in large-scale AI benchmarks and contests
- Multiple years of experience in developing and deploying machine learning solutions in distributed SW development teams
- Demonstrated capability to go beyond research prototypes and integrate cutting-edge AI methods into practically relevant and usable SW solutions
- Multimodal AI & Vision-Language Models:
- Proficiency in designing and training vision-language models (VLMs) and language-multimodal models (LMMs) (e.g. Flamingo GPT-4V PaLM-E RT-2)
- Hands-on experience with visual grounding cross-modal attention and instruction-following architectures
- Familiarity with benchmarks such as ALFRED Ego4D VLN or datasets involving perception and action
- Control Reinforcement Learning & Planning:
- Strong experience in reinforcement learning imitation learning or model-based control for agents operating in real or simulated environments
- Capability in designing agents for long-horizon planning semantic task decomposition and hierarchical control
- Knowledge of methods that combine perception language and action in task-driven settings
- AI for Cyber-Physical Systems & Automation:
- Demonstrated capability to integrate cutting-edge AI methods into practical applications in robotics automated
- driving industrial automation or building systems interest in emerging domains such as smart heating and HVAC control where semantic AI can optimize control strategies
- Focus on building robust explainable and semantically grounded agents for physical deployment
- Infrastructure Simulation & Tooling:
- Proficient in Python and deep learning libraries such as PyTorch TensorFlow or JAX
- Experience with simulation platforms such as Isaac Sim CARLA MuJoCo or Habitat
- Skilled in developing scalable pipelines using Docker CI/CD and multi-GPU/cloud infrastructure
- Proven ability to drive research projects and turning research into practical innovation
- Collaborative and interdisciplinary mindset able to work across research and product teams at Bosch
- Personality and Working Practice: you have proven ability to drive research projects and turning research into practical innovation; collaborative and interdisciplinary mindset you are able to work across research and product teams at Bosch
- Languages: fluent English German is optional
Additional Information :
submit all relevant documents (CV certificates and links to GitHub or kaggle account).
We offer flexible working models: from various part-time options to mobile working and job sharing. Feel free to contact us.
Diversity and inclusion are not just trends for us but are firmly anchored in our corporate culture. Therefore we welcome all applications regardless of gender age disability religion ethnic origin or sexual identity.
Need support during your application
Meltem Arabacioglu (Human Resources)
Need further information about the job
Jim Mainprice (Functional Department)
49 9
Michael Pfeiffer (Functional Department)
49 5
Remote Work :
No
Employment Type :
Full-time
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