Principal Machine Learning Engineer
Tasks
- Apply NLP techniques for production applications
- Architect and implement LLM powered systems for multi cloud
- Conduct A B testing and measure performance improvements
- Containerize and deploy ML services
- Deploy and manage models in production
- Design and deploy machine learning and LLM solutions for production
- Develop end-to-end ML pipelines
- Implement and maintain MLOps best practices
- Optimize ML workflows for performance scalability reliability and cost
- Train and evaluate deep learning models
Perks/Benefits
Skills/Tech-stack
A/B | A/B Testing | AWS | Attention Mechanisms | Automated retraining | Azure | B testing | CI/CD | Cloud Computing | Data Ingestion | Docker | Embeddings | Experiment tracking | Feature Engineering | GCP | Generative AI | Kubernetes | LLM Agents | Language Models | Large Language Models | MLOps | Machine Learning | Model Evaluation | Model Monitoring | Model Training | Model versioning | NLP | PyTorch | Python | Statistical Analysis | TensorFlow | Transformers
Education
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