Senior Machine Learning Engineer
Tasks
- Apply MLOps and AIOps practices
- Build scalable ML architectures
- Deploy models to production
- Design and develop machine learning models
- Develop data and model pipelines
- Implement continuous monitoring and retraining
- Mentor engineering teams
- Perform feature engineering
- Run hyperparameter tuning
- Support AI experimentation and model evaluation
- Train, validate, and optimize models
- Translate client business needs into ML solutions
Perks/Benefits
Skills/Tech-stack
AIOps | AWS | Amazon SageMaker | Apache Airflow | Azure | Azure Databricks | Azure Machine Learning | Cloud platform | Data Drift | Deep learning | Docker | Feature Engineering | Fine Tuning | Google Cloud | Google Cloud Platform | Google Vertex | Google Vertex AI | Hugging Face | Hyperparameter Tuning | Kubeflow | Kubernetes | Langchain | MLOps | MLflow | Machine Learning | Model Monitoring | OpenAI | Pandas | Pinecone | Prompt engineering | PyTorch | Python | RAG | Scikit-learn | TensorFlow | Transformers | Vector Databases | Vertex AI | Weaviate | XGBoost
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
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