AI Research Engineer (Multi-Modal & Vision)
Tasks
- Apply knowledge distillation
- Apply reinforcement learning from human feedback
- Build multimodal datasets
- Collaborate on research publications
- Conduct vision language model research and development
- Design and implement supervised fine-tuning
- Develop benchmarking systems and evaluation frameworks
- Implement distributed training workflows
- Monitor multimodal learning research
- Optimize models for efficiency and scalability
Perks/Benefits
- Autonomy and ownership
- Flexible working arrangements
- Fully remote
- Professional growth opportunities
- Publication support
- Work-life balance
Skills/Tech-stack
Benchmarking | Dataset curation | Distributed Training | Efficient Fine Tuning | Evaluation Frameworks | Fine Tuning | GPU Training | Hugging Face | Human Feedback | Knowledge Distillation | Learning from Human Feedback | Model Compression | Model Optimization | Open Source | Parameter efficient fine-tuning | Reinforcement Learning | Reinforcement Learning from Human Feedback | Supervised Fine Tuning
Education
Roles
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