Description
You will design and architect scalable AI platforms to develop and deploy solutions using ML and Deep Learning techniques.
Responsibilities
- Architect scalable AI platforms and lead infrastructure setup, including cloud services and data pipelines.
- Collaborate with stakeholders and engineering teams to gather requirements for AI use cases.
- Define and implement AI/ML architecture best practices, frameworks, and standards.
- Optimize AI/ML workflows for performance, cost efficiency, and resource utilization.
- Design and implement data governance, security, and compliance measures for production environments.
Required Skills
- 5+ years of experience in AI/ML platform architecture.
- Deep understanding of ML algorithms and Deep Learning architectures.
- Proficiency with TensorFlow, PyTorch, and Scikit-Learn.
- Experience with cloud platforms including GCP and Azure.
- Hands-on experience with Docker and Kubernetes.
- Expertise in container orchestration using AKS, GKE, or OpenShift.
- Strong knowledge of the model development life cycle and software engineering principles.
- Experience designing distributed computing systems for AI/ML workloads.
- Familiarity with DevOps practices and CI/CD pipelines.