AI Research Engineer (Multi-Modal & Vision)
Tasks
- Build and maintain multimodal datasets
- Collaborate on research publications
- Conduct end to end research and development of vision language models
- Contribute to open source AI ecosystems
- Design and implement knowledge distillation
- Design and implement post training supervised fine tuning
- Design and implement reinforcement learning from human feedback
- Develop benchmarking systems and evaluation frameworks
- Implement distributed training workflows
- Monitor multimodal research advancements
- Optimize model efficiency and scalability
Perks/Benefits
- Flexible working arrangements
- High autonomy
- Professional growth opportunities
- Remote work
- Research publication support
Skills/Tech-stack
Benchmarking | Distributed Training | Efficient Fine Tuning | Fine Tuning | GPU infrastructure | Hugging Face | Human Feedback | Knowledge Distillation | Language Models | Learning from Human Feedback | Machine Learning | Machine Learning Pipelines | Model Compression | Model Optimization | Multimodal Learning | Open Source | Parameter efficient fine-tuning | PyTorch | Python | Reinforcement Learning | Reinforcement Learning from Human Feedback | Supervised Fine Tuning | Vision Language Models | Vision-language
Education
Roles
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