Machine Learning Engineer, Trust & Safety
Tasks
- Apply AI and machine learning for trust and safety detection
- Build data pipelines
- Build inference pipelines
- Build machine learning models
- Collaborate with AI platform team
- Collaborate with backend engineers
- Collaborate with data engineers
- Collaborate with data scientists
- Collaborate with product managers
- Deploy machine learning models
- Design and run offline and online metrics evaluations
- Design model evaluations for fairness and safety
- Detect policy violating actors
- Evaluate model effectiveness
- Iterate on model improvements
- Maintain machine learning models
- Monitor model performance
- Refine models using business impact signals
- Refine models using user feedback
- Remove harmful content
- Test models for risk
Perks/Benefits
- 401k matching
- Date stipend
- Employee resource groups
- Fertility support
- Free Hinge Premium access
- Learning and development stipend
- Paid parental leave
- Udemy access
Skills/Tech-stack
Content Classification | Data Pipelines | Databricks | Deep learning | Distributed Computing | False Positive | False Positive Rate | Feature Store | Fraud Detection | Hallucination | Hugging Face | Hugging Face Transformers | Kubeflow | Kubernetes | LLM | Machine Learning | Model Serving | Observability | Precision Recall F1 | Precision-recall | PyTorch | Python | RAG | Ray | SQL | Spark | Workflow Orchestrator
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
Regions
Countries
States
Cities
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