AI Research Engineer (Multi-Modal & Vision)
Tasks
- Build and maintain distributed training workflows
- 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 reinforcement learning from human feedback
- Design and implement supervised fine-tuning
- Develop benchmarking systems and evaluation frameworks
- Identify and resolve GPU performance bottlenecks
- Monitor multimodal research and translate into improvements
- Optimize and compress machine learning models
Perks/Benefits
- Flexible working hours
- Professional growth opportunities
- Publication support
- Remote work
- Work-life balance
Skills/Tech-stack
Benchmarking | Distributed Training | Efficient Fine Tuning | Evaluation Frameworks | Fine Tuning | GPU Computing | GitHub | Hugging Face | Human Feedback | Knowledge Distillation | Language Models | Learning from Human Feedback | Model Compression | Model Optimization | Multimodal AI | Open Source | Open-Source Development | Parameter efficient fine-tuning | Pipeline Development | Reinforcement Learning | Reinforcement Learning from Human Feedback | Source development | Supervised Fine Tuning | Training Pipeline | Training pipeline development | Vision Language Models | Vision-language
Education
Roles
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