Machine Learning Engineer, Embedding
Tasks
- Collaborate across research product and infrastructure teams end to end ownership
- Design and build vector search systems and embedding serving infrastructure
- Design distributed training pipeline for multimodal embedding models
- Design evaluation metrics and solve applied research problems
- Improve and automate ML pipeline from model development training to serving
- Optimize inference performance for embedding models
- Use AI developer tools to increase development productivity
Perks/Benefits
Skills/Tech-stack
Batch Processing | Computer Vision | Contrastive Learning | Distributed Training | Embedding Models | Faiss | GPU Memory Optimization | GPU memory | Inference Optimization | Inference Server | Kubernetes | Language Processing | Machine Learning | Memory Optimization | Milvus | Model Serving | Multimodal Learning | Natural Language | Natural Language Processing | PyTorch | Python | Quantization | Representation Learning | ScaNN | TensorRT | Triton Inference | Triton Inference Server | VLLM | Vector Search
Education
N/A
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