Lead-ML Engineer
Tasks
- Build RAG pipelines
- Build scalable ML pipelines
- Conduct prompt iteration for LLM performance
- Deploy ML models to production
- Design ML and GenAI applications
- Design ML model architecture
- Develop prompt templates for LLMs
- Develop vector search systems
- Evaluate and tune machine learning models
- Implement agentic workflows
- Perform data cleaning and preprocessing
- Serve LLM inference
- Train and fine-tune ML models
Perks/Benefits
- N/A
Skills/Tech-stack
Computer Vision | Data Analysis | Data Augmentation | Data Preprocessing | Data Warehousing | Deep learning | Exploratory Data Analysis | Feature Engineering | Fine Tuning | Google Cloud | Inference Serving | Langchain | Language Processing | Learning operations | Machine Learning | Machine Learning Operations | Model Evaluation | Model Fine-tuning | Model Training | Natural Language | Natural Language Processing | NumPy | Pandas | Prompt engineering | PyTorch | Python | Retrieval-Augmented Generation | Scikit-learn | TensorFlow | Vector Search | XGBoost
Education
N/A
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