PhD Research Internship – Robotics Engineer (VLM / VLA Models)
Tasks
- Apply parameter efficient fine tuning
- Benchmark models against baselines
- Build and extend Vision Language Models
- Collaborate to deploy prototypes into production systems
- Design and develop Vision Language Action systems
- Design evaluation protocols for embodied AI
- Develop self supervised or weakly supervised dataset pipelines
- Document findings for publications technical reports or patents
- Explore scalable multi modal reasoning architectures
- Ground actions for real world execution
- Lead multi modal dataset design and analysis
- Optimize models for real time inference robustness and safety
- Optimize prompts and reasoning augmentation
- Present results internally and at conferences
- Run large scale experiments and analyze results
- Use alignment methods for model training
Perks/Benefits
Skills/Tech-stack
Control Systems | Deep learning | Distributed Training | Efficient Fine Tuning | Embodied AI | Fine Tuning | Language Models | Machine Learning | Model Alignment | Multi-Modal | Multi-Modal Learning | Parameter efficient fine-tuning | Prompt engineering | PyTorch | Python | Real Time | Real-time Inference | Robotics | Self-Supervised Learning | Self-supervised | Sensor fusion | Supervised Learning | Vision Language Models | Vision-language | Vision-language-action | Weakly-Supervised Learning
Education
Roles
AI | AI Research Intern | Engineer | Intern | Research Intern | Robotics Engineer
Regions
Countries
States
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