AI/ML Engineer
Tasks
- Automate model retraining
- Build automated model evaluation systems
- Build data pipelines for ingestion and transformation
- Build retrieval-augmented generation pipelines
- Conduct model experiments and evaluations
- Deploy machine learning and AI models
- Design machine learning models
- Detect anomalies in model outputs
- Develop machine learning and AI models
- Enable semantic search and intelligent retrieval
- Implement model fine-tuning
- Integrate ML models into production systems
- Integrate and optimize AI models
- Monitor model performance
- Perform prompt engineering
- Preprocess data for model training
- Present insights to stakeholders
- Use vector databases and embeddings
Perks/Benefits
- Collaborative work environment
- Competitive compensation
- Continuous learning opportunities
- Growth-oriented culture
Skills/Tech-stack
AWS | Anomaly Detection | Automated retraining | Azure | Chroma | Data Preprocessing | Embeddings | Faiss | Feature Engineering | Fine Tuning | GCP | Generative AI | Hugging Face | Langchain | Llamaindex | MLOps | Model Evaluation | Model Fine-tuning | NumPy | Open Source | Open-source Models | OpenAI | Pandas | Pinecone | Prompt engineering | PyTorch | Python | Retrieval-Augmented Generation | Scikit-learn | TensorFlow | Vector Databases
Education
N/A
Roles
AI | AI/ML Engineer | Engineer | ML Engineer
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