VLM Engineer
Tasks
- Annotate geospatial imagery data
- Build multimodal evaluation pipelines
- Collaborate on model architecture iterations
- Compute task specific metrics
- Configure AWS training infrastructure
- Curate and transform geospatial datasets
- Deploy model endpoints on AWS
- Design fine-tuning pipelines
- Develop evaluation frameworks
- Implement LoRA and QLoRA adapters
- Implement distributed fine tuning
- Optimize hyperparameters
- Optimize inference performance
- Optimize training cost
- Orchestrate model training
- Preprocess training data
- Select EC2 GPU instances
Perks/Benefits
- N/A
Skills/Tech-stack
AWS | Automated metrics | Benchmarking | CI/CD | CLIP | Computer Vision | DPO | Data Preprocessing | Data Processing | Deep learning | DeepSpeed | Distributed Training | EC2 | FSDP | Fine Tuning | GPU Training | Geospatial Data | Geospatial Data Processing | HuggingFace Accelerate | HuggingFace Datasets | HuggingFace PEFT | HuggingFace Transformers | Hyperparameter Optimization | Inference Optimization | Instruction Tuning | LLaVA | LoRA | Machine Learning | Megatron | Model Evaluation | Multimodal Models | PyTorch | Python | QLoRA | RLHF | SageMaker | Supervised Fine Tuning | Testing | Version control | ViT | Vision Transformer
Education
N/A
Roles
AI | AI Engineer | Engineer | Learning Engineer | Machine Learning Engineer
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