AI / ML Engineer

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