Senior Software Engineer, Applied ML
Tasks
- Apply LLMs to interpret unstructured data
- Build and evolve backend and ML systems
- Define architecture testing and monitoring standards
- Develop data pipelines and processing
- Engineer features and model tooling
- Implement real time fraud detection and identity protection
- Mentor engineers via code and architecture reviews
- Own end to end delivery of ML initiatives
- Partner with data science and product engineering on data and ML strategy
Perks/Benefits
- 401k
- Commuter benefits
- Dependent care FSA
- Employee assistance programs
- Fitness benefits
- Flexible time off
- Medical and dental and vision premiums covered
- Mental health apps
- Paid Holidays
- Parental leave
- Stock options
- Team-building activities
Skills/Tech-stack
Algorithms | BigQuery | Cloud Storage | Cloud platform | Data Structures | Dataflow | Feature Engineering | Google Cloud | Google Cloud Platform | Google Cloud Storage | Google Kubernetes | Google Kubernetes Engine | Google Spanner | Java | Kubeflow | Kubernetes | Kubernetes Engine | LLM | Machine Learning | Microservices | Model Deployment | MongoDB | Monitoring | NoSQL | Object-Oriented | Object-oriented design | PubSub | Python | Relational databases | SageMaker | Scala | Testing | Vertex AI
Education
Regions
Countries
States
Cities
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