Principal ML Engineer, ML Platform Engineering
Tasks
- Build and maintain REST APIs
- Champion adoption of ML engineering technologies and methodologies
- Collaborate with product managers, data scientists, and leadership
- Create technical documentation and diagrams
- Deliver ML infrastructure and software meeting customer requirements
- Design and deploy cloud infrastructure for ML
- Develop ML infrastructure using Infrastructure as Code
- Implement machine learning lifecycle infrastructure
- Lead ML engineering by coding and troubleshooting
- Perform code review and provide mentorship
Perks/Benefits
- 401k match
- Dental insurance
- Disability insurance
- EAP
- Employee assistance program
- Life insurance
- Medical insurance
- Paid time off
- Vision insurance
Skills/Tech-stack
A/B | A/B Testing | API Design | Amazon ECR | Amazon Web Services | Automated retraining | B testing | CloudWatch | Continuous integration | Data Processing | Deep learning | Docker | Drift Detection | EKS | Feature Store | Functional Programming | GPT | IAM | Infrastructure as Code | Kinesis | Kubernetes | LLM | Lambda | Language Models | Large Language Models | Machine Learning | Model Drift | Model Drift Detection | Model registration | Multimodal Data | Multimodal Data Processing | Object-Oriented | Object-oriented programming | PyTorch | Python | REST API | REST API design | SageMaker | Service Catalog | TensorFlow | Terraform | Transformers | Version control | Vision Language Models | Vision-language | Web Services | “as-code”
Education
Regions
Countries
States
Cities
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