ML Engineer
Tasks
- Build data pipelines
- Create evaluation frameworks
- Deploy machine learning systems
- Design machine learning models
- Develop LLM based AI applications
- Fine-tune LLMs
- Implement embeddings and retrieval techniques
- Implement prompting strategies
- Monitor deployed models
- Optimize models for production
Perks/Benefits
- N/A
Skills/Tech-stack
Distillation | Distributed Training | Efficient Fine Tuning | Embeddings | Fine Tuning | GPU Optimization | Hugging Face | Hugging Face Transformers | Human Feedback | Inference Optimization | Language Models | Language Processing | Large Language Models | Learning from Human Feedback | LoRA | MLOps | Machine Learning | Model Deployment | Model Evaluation | Model Monitoring | Natural Language | Natural Language Processing | Parameter efficient fine-tuning | Prompt engineering | PyTorch | Python | Quantization | RAG | Reinforcement Learning | Reinforcement Learning from Human Feedback | Semantic Search | Supervised Fine Tuning | TensorFlow | Tokenization | Transformers | Vector Databases
Education
N/A
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