ML Engineer (Data)
Tasks
- Analyze data and machine learning models to identify insights and improvements
- Deploy machine learning models using MLOps
- Develop classical machine learning and deep learning models
- Fine-tune and integrate Large Language Models
- Implement CI CD pipelines for ML deployments
- Monitor model drift and model performance in production
- Optimize models for performance and latency
Perks/Benefits
Skills/Tech-stack
Amazon SageMaker | Apache Spark | BERT | CI/CD | Caching | Cloud platform | Dask | Deep learning | Docker | Drift Detection | Feature Engineering | Fine Tuning | GPT | Google Cloud | Google Cloud Platform | Grafana | Hugging Face | Kubeflow | Kubernetes | LLM Fine-tuning | Linux | MLOps | MLflow | Machine Learning | Microsoft Azure | Model Drift | Model Drift Detection | Model Monitoring | Pandas | Prometheus | PyTorch | Python | Scikit-learn | TensorFlow | Transformers
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
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