AI Research Engineer (Multi-Modal & Vision)
Tasks
- Build and maintain multimodal datasets
- Collaborate on research publications and submissions
- Conduct end to end research and development for vision language models
- Contribute to open source AI ecosystems
- Design and implement post training methodologies
- Develop benchmarking systems and evaluation frameworks
- Implement distributed training workflows on GPU infrastructure
- Monitor multimodal research and translate into improvements
- Optimize model efficiency and scalability
Perks/Benefits
- Autonomy
- Flexible working arrangements
- Professional growth
- Publication support
- Remote work
- Work-life balance
Skills/Tech-stack
Benchmarking | Data Curation | Dataset Filtering | Distributed Training | Efficient Fine Tuning | Evaluation Frameworks | Fine Tuning | GPU Computing | Human Feedback | Knowledge Distillation | Learning from Human Feedback | Machine Learning | Machine Learning Pipelines | Model Compression | Model Optimization | Multimodal AI | Open Source | Parameter efficient fine-tuning | Reinforcement Learning | Reinforcement Learning from Human Feedback | Supervised Fine Tuning | Vision-language
Education
Bachelor of Engineering | Bachelor of Science | Master of Science | PhD
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