Senior AI/ML Engineer
Tasks
- Architect cloud or containerized AI ML operations
- Build automated model training validation testing deployment monitoring pipelines
- Collaborate with cybersecurity for security access control auditing and governance
- Conduct technical reviews and mentor engineers and data scientists
- Define MLOps standards and reusable patterns
- Design model serving platforms for batch and real time inference
- Establish model versioning artifact management reproducibility and data lineage
- Implement model monitoring drift detection explainability and governance
- Lead AI ML architecture and evolution
- Set up CI CD infrastructure as code automated testing and source control
Perks/Benefits
- 401k match
- Flexible PTO
- Flexible spending account
- Health, dental, and vision insurance
- Paid Cloud Developer Accounts
- Paid federal holidays
- Professional development training certifications conferences
Skills/Tech-stack
AWS | Automated testing | Azure | CI/CD | Containerization | Data Lineage | Data Versioning | Deep learning | Docker | Drift Detection | Explainability | Feature Engineering | Google Cloud | Infrastructure as Code | Kubernetes | MLOps | Machine Learning | Model Drift | Model Drift Detection | Model Monitoring | Python | Source Control | “as-code”
Education
Roles
AI/ML Engineer | Engineer | ML Engineer | Senior AI/ML Engineer
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