Applied Scientist 5
Tasks
- Build image video understanding pipelines
- Collaborate with product research and infrastructure teams
- Define evaluation frameworks benchmarks and human preference studies
- Design distributed training infrastructure
- Design train fine tune diffusion models
- Develop and fine tune vision foundation models
- Improve sampling efficiency
- Integrate vision encoders with generative backbones
- Lead technical design reviews write engineering RFCs set quality standards
- Mentor ML engineers through code reviews and pair programming
- Optimize inference with quantization ONNX export Flash Attention xFormers
- Own ML lifecycle data curation experiment tracking evaluation optimization deployment monitoring
Perks/Benefits
- N/A
Skills/Tech-stack
3D Reconstruction | Adapters | CLIP | Computer Vision | ControlNet | DDIM | DDP | DDPM | DINOv2 | DPO | DVC | DeepSpeed | Depth Estimation | DiT | Diffusion Models | Distributed Training | Experiment tracking | FP8 | FSDP | Flash Attention | Generative Modeling | INT8 | IP-Adapter | Image Editing | Information theory | Inpainting | LDM | LoRA | MLOps | MLflow | Megatron-LM | Model Evaluation | Monitoring | ONNX | Object Detection | Optical Flow | Probabilistic ML | PyTorch | Python | Quantization | RLHF | SAM | Segmentation | Variational Inference | ViT | Weights and Biases | XFormers
Education
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