AI Research Engineer (Multi-Modal & Vision) - 100% Remote Worldwide
Tasks
- Build and scale training workflows with distributed GPUs
- Conduct end to end research on vision language models
- Contribute to open source multimodal ecosystems
- Design and implement evaluation frameworks
- Design and implement post training pipelines
- Develop and maintain multimodal datasets
- Drive model efficiency and deployability
- Identify and resolve training pipeline bottlenecks
- Publish research findings
- Translate research into practical improvements
Perks/Benefits
Skills/Tech-stack
Benchmarking | Data Balancing | Data Filtering | Dataset curation | Distributed Training | Efficient Fine Tuning | Evaluation Frameworks | Fine Tuning | GPU Training | GitHub | Huggingface | Human Feedback | Knowledge Distillation | Language Models | Learning from Human Feedback | Model Compression | Model Optimization | Multimodal Learning | Open Source | Open-source contributions | Parameter efficient fine-tuning | Pipeline Optimization | Reinforcement Learning | Reinforcement Learning from Human Feedback | Supervised Fine Tuning | Training Pipeline | Training pipeline optimization | Vision Language Models | Vision-language
Education
Roles
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