AI Research Engineer (Multi-Modal & Vision)
Tasks
- Build and maintain multimodal datasets
- Collaborate on research publications
- Conduct end to end research and development
- Contribute to open source AI ecosystems
- Design and implement post training methodologies
- Develop benchmarking and evaluation frameworks
- Implement distributed training workflows
- Monitor emerging multimodal research
- Optimize and compress AI models
Perks/Benefits
- Autonomy
- Flexible working arrangements
- High-impact projects
- Professional growth opportunities
- Publication support
- Remote work
- Work-life balance
Skills/Tech-stack
Benchmarking | Dataset curation | Distributed Training | Efficient Fine Tuning | Fine Tuning | GPU infrastructure | Human Feedback | Knowledge Distillation | Learning from Human Feedback | Machine Learning | Machine Learning Pipelines | Model Compression | Model Optimization | Multimodal Learning | Network evaluation | Neural Network | Neural network evaluation | Open Source | Parameter efficient fine-tuning | Reinforcement Learning | Reinforcement Learning from Human Feedback | Supervised Fine Tuning | Vision-language
Education
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