AI Research Engineer (Multi-Modal & Vision)
Tasks
- Build and maintain multimodal datasets
- Conduct vision language model research
- Contribute to open source AI ecosystems
- Design and implement post training methodologies
- Develop benchmarking and evaluation frameworks
- Implement distributed training workflows
- Improve model performance on benchmarks
- Optimize and compress models for deployment
- Support research publications
- Translate research into production improvements
Perks/Benefits
- Flexible working arrangements
- Fully remote work
- Professional growth opportunities
- Publication support
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 | Machine Learning | Machine Learning Pipelines | Model Compression | Model Optimization | Multimodal Learning | 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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