Senior Machine Learning Engineer
Tasks
- Build data ingestion and training pipelines
- Build reusable model components
- Conduct design and code reviews
- Create extensible machine learning library modules
- Define offline and online model metrics
- Deploy ML models and manage real time monitoring
- Design end-to-end ML systems
- Identify technical risks including data leakage and hardware constraints
- Implement build vs buy trade offs
- Partner with data scientists to improve experimental code
- Provide models for adoption by other product teams
- Translate clinical and product objectives into computational tasks
- Turn experiments into repeatable platform capabilities
Perks/Benefits
- Enhanced parental leave
- Fertility support
- Flexible working
- Free meals and snacks
- Generous paid time off
- Healthcare coverage
- Life insurance
- Parental loss support
- Pension
- Share options
- Work from anywhere
Skills/Tech-stack
Amazon SageMaker | Bayesian Methods | C# | Data Versioning | Data handling | Data leakage | Deep learning | Differential Privacy | Fine Tuning | GDPR | Go | Google Vertex | Google Vertex AI | HIPAA | Infrastructure as Code | Jupyter | Kubernetes | Language Models | Language Processing | Large Language Models | MLOps | Machine Learning | Model Serving | Natural Language | Natural Language Processing | Prompt engineering | Python | Secure Data | Secure Data Handling | Terraform | Transformers | Tree-based Models | Vertex AI | “as-code”
Education
N/A
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