AIML Engineer
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Job Location:
Scottsdale, AZ - USA
Monthly Salary:
Not Disclosed
Posted on:
30+ days ago
Vacancies:
1 Vacancy
Job Summary
Key Responsibilities:
Design implement and maintain ML pipelines for training testing and deploying AIML models.
Manage and optimize cloud-based ML infrastructure (GCP Vertex AI AWS SageMaker or equivalent).
Implement CICD pipelines for ML and AI-driven applications.
Monitor troubleshoot and optimize model performance and system reliability.
Automate workflows for data ingestion model training deployment and monitoring.
Collaborate with cross-functional teams to ensure secure scalable and compliant ML operations.
Apply MLOps best practices for reproducibility versioning and governance of ML models.
Required Qualifications:
5 years experience in DevOps CloudOps or ML Ops.
5 years experience with GCP AIML services (Vertex AI AI Platform BigQuery ML) or AWS ML services (SageMaker etc).
5 years Experience with containerization and orchestration (Docker Kubernetes).
Proficiency in infrastructure-as-code (Terraform CloudFormation or Deployment Manager). Familiarity with CICD pipelines (Jenkins GitHub Actions GitLab CI or ArgoCD).
Strong programming skills in Python Bash or Go with experience in ML frameworks (TensorFlow PyTorch Scikit-learn).
Preferred Certifications (one or more):
Google Cloud Professional Machine Learning Engineer
Google Cloud Professional Data Engineer
AWS Certified Machine Learning Specialty
Certified Kubernetes Admin(CKA)
Google Professional Cloud Architect
Design implement and maintain ML pipelines for training testing and deploying AIML models.
Manage and optimize cloud-based ML infrastructure (GCP Vertex AI AWS SageMaker or equivalent).
Implement CICD pipelines for ML and AI-driven applications.
Monitor troubleshoot and optimize model performance and system reliability.
Automate workflows for data ingestion model training deployment and monitoring.
Collaborate with cross-functional teams to ensure secure scalable and compliant ML operations.
Apply MLOps best practices for reproducibility versioning and governance of ML models.
Required Qualifications:
5 years experience in DevOps CloudOps or ML Ops.
5 years experience with GCP AIML services (Vertex AI AI Platform BigQuery ML) or AWS ML services (SageMaker etc).
5 years Experience with containerization and orchestration (Docker Kubernetes).
Proficiency in infrastructure-as-code (Terraform CloudFormation or Deployment Manager). Familiarity with CICD pipelines (Jenkins GitHub Actions GitLab CI or ArgoCD).
Strong programming skills in Python Bash or Go with experience in ML frameworks (TensorFlow PyTorch Scikit-learn).
Preferred Certifications (one or more):
Google Cloud Professional Machine Learning Engineer
Google Cloud Professional Data Engineer
AWS Certified Machine Learning Specialty
Certified Kubernetes Admin(CKA)
Google Professional Cloud Architect
Key Skills
- ASP.NET
- Health Education
- Fashion Designing
- Fiber
- Investigation
