Applied AI Engineer
Tasks
- Build RAG and agent orchestration
- Build data flywheel for labeling and data versioning
- Build real time streaming voice pipelines
- Create evaluation harnesses for model regressions
- Deploy ML models across cloud and edge
- Fine tune and retrain models with LoRA and PEFT
- Implement data collection and labeling pipelines
- Integrate foundation models into production pipelines
Perks/Benefits
Skills/Tech-stack
ASR | AWS SageMaker | Active Learning | Azure ML | DVC | Deep learning | Edge ML | Embeddings | Fine Tuning | Inference Runtime | Language Models | Large Language Models | Llama.cpp | LoRA | MLOps | MLflow | Machine Learning | ONNX | PEFT | Python | Quantization | RAG | Streaming | Supervised Fine Tuning | TTS | TensorRT | VLLM | Vertex AI | Vision Language Models | Vision-language | Weights and Biases
Education
N/A
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