LLM Engineer
Tasks
- Apply AI best practices in regulated environments
- Benchmark models and support continuous improvement
- Build LLM powered applications and AI assistants
- Build scalable training and inference pipelines
- Combine LLMs with retrieval systems and external tools
- Develop and deploy machine learning and deep learning models
- Develop data pipelines for dataset curation and preprocessing
- Ensure models are robust and production ready
- Evaluate and optimize LLM performance
- Integrate models into platform workflows
- Train and fine-tune LLMs
Perks/Benefits
Skills/Tech-stack
AI Safety | AWS | Azure | Benchmarking | CI | CI/CD | Deep learning | Distributed Training | Embedding Models | Fine Tuning | Hugging Face | Instruction Tuning | LLMOps | MLflow | Machine Learning | Model Alignment | Model Evaluation | Model Fine-tuning | NLP | Prompt engineering | PyTorch | Python | RAG | Retrieval systems | Transformer | Vector Databases | Weights and Biases
Education
N/A
Roles
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