Applied AI Engineer
Tasks
- Architect internal API layers and shared services
- Automate infrastructure provisioning and configuration with infrastructure as code
- Build proof of concepts for anomaly detection and troubleshooting
- Containerize and orchestrate AI workloads with Docker and Kubernetes
- Develop AI powered tooling for internal workflows
- Develop and iterate on MLOps pipelines
- Establish AI development patterns and best practices
- Own and extend AI platforms and tooling
Perks/Benefits
- Medical, dental & vision coverage
- Nutritionist
- PTO paid by company
- Paid time off
- Volunteer PTO
- Workout lunches
Skills/Tech-stack
AWS | Ansible | Artifactory | CI/CD | Docker | EC2 | ECS | EKS | GitHub Actions | IAM | Inference Optimization | Kubernetes | Lambda | MLOps | Machine Learning | Model Serving | Prompt engineering | Python | RAG | RDS | REST APIs | Retrieval-Augmented Generation | S3 | Semantic Search | Terraform | TypeScript | VPC | Vector Databases
Education
Bachelor of Engineering | Bachelor of Engineering in Computer Science | Bachelor of Science | Bachelor of Science in Computer Science
Roles
Regions
Countries
States
Cities
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