Senior Staff Applied ML Engineer
Tasks
- Analyze data using Python
- Build and tune machine learning models
- Define data and ML best practices and templates
- Design AI ingest workflows
- Implement auto fill and suggestion workflows
- Implement user request routing and enrichment
- Integrate models into production systems
- Mentor junior data and ML engineers
- Monitor model performance and reliability
- Productionize machine learning models
- Provide architecture guidance for data and ML features
- Review code and model work
- Surface similar past items
- Transform unstructured inputs into structured data
Perks/Benefits
- N/A
Skills/Tech-stack
APIs | Amazon SageMaker | Classification | Clustering | Dimensionality Reduction | Embeddings | Factor models | Feature Engineering | Fine Tuning | Google Vertex | Google Vertex AI | Kubeflow | LLM | Latent factor models | MLOps | MLflow | Matrix Factorization | Microservices | Model Evaluation | Model Monitoring | Pandas | Prompt engineering | PySpark | PyTorch | Python | RAG | SQL | Scikit-learn | Supervised Learning | Vertex AI
Education
N/A
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