Applied Scientist 5.5
Tasks
- Architect diffusion based models
- Build production image video perception pipelines
- Collaborate across product research and infrastructure teams
- Define evaluation frameworks benchmarks and human preference studies
- Deploy distributed training on GPU clusters
- Design train and fine tune diffusion models
- Develop vision foundation models
- Improve diffusion sampling efficiency
- Integrate vision encoders with generative backbones
- Lead technical design reviews write engineering RFCs set quality standards
- Mentor engineers through code reviews and pair programming
- Optimize inference with quantization and ONNX export
- Own ML lifecycle data curation experiment tracking model evaluation optimization deployment monitoring
Perks/Benefits
- N/A
Skills/Tech-stack
3D Reconstruction | Adapters | CLIP | Computer Vision | ControlNet | Convolutional Neural Networks | DDP | DINOv2 | DPO | DVC | Data Curation | DeepSpeed | Deployment | Depth Estimation | Diffusion Models | Distributed Training | Editing | Experiment tracking | FSDP | Flash Attention | Generative Modeling | IP-Adapter | Information theory | Inpainting | LoRA | MLOps | MLflow | Megatron-LM | Model Evaluation | Model Optimization | Monitoring | Neural Networks | Normalizing flows | ONNX | Object Detection | Optical Flow | PyTorch | Python | Quantization | RLHF | Renaissance of flows | Segmentation | Variational Inference | ViT | Vision Transformers | Weights and Biases | XFormers
Education
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