IT Cloud Architect mlops

Khối / Ban
- Khối Dịch vụ Công nghệ Ngân hàng
- Lĩnh vực
- Công nghệ thông tin
- Địa điểm
- Hồ Chí Minh
- Loại hình công việc
- Fulltime (toàn thời gian)
- Thời hạn ứng tuyển
- 31/03/2025
- Số lượng cần tuyển
- 1
- Mô tả công việc

**Key Responsibilities**: Responsible for (i) building and running AI/ML systems on cloud platforms like AWS, GCP, and Azure (ii) creating and using tools to automate the process of building, training, and deploying AI/ML models (iii) making sure the AI/ML systems run smoothly and efficiently.
- Design, implement, and optimize highly scalable and fault-tolerant cloud architectures (AWS, GCP, Azure, or hybrid) for AI/ML solutions, ensuring best practices in security, cost management, and compliance.
- Develop and maintain robust MLOps frameworks to automate the entire AI/ML lifecycle, from data ingestion and model training to deployment and monitoring.
- Collaborate with data scientists and engineers to build repeatable processes for model experimentation, validation, and deployment, ensuring high availability and scalability in production environments. Work closely with DevOps, Data Science, and Engineering teams to ensure smooth deployment, scalability, and operational excellence of ML solutions.
- Design and implement comprehensive model monitoring, logging, and feedback mechanisms to track performance, identify data drift, and manage re-training requirements.
- Optimize model performance and resource allocation to minimize latency, maximize efficiency, and reduce costs.
- Leverage Infrastructure-as-Code (IaC) tools (e.g., Terraform, CloudFormation) to automate the provisioning and management of cloud resources. Utilize containerization (Docker) and orchestration platforms (Kubernetes) for efficient management of ML workflows and services.
- Integrate CI/CD pipelines for seamless deployment of model code and infrastructure changes.
- Implement robust backup, disaster recovery, and failover strategies for critical cloud-based AI/ML services.
- Stay abreast of the latest trends and technologies in cloud computing, AI/ML, and MLOps, evaluating and implementing emerging tools and techniques to enhance performance and reduce costs.
- Perform other tasks as assigned by the manager.

**Requirements**:

- Bachelor‘s degree in Computer Science, AI/ML, or a related field.
- Minimum 7 years (Principle Cloud Architect)/5 years (Senior Cloud Architect)/3 years (Cloud Architect) experience with cloud services related to AI/ML (e.g., AWS Sagemaker, GCP AI Platform, Azure Machine Learning) and strong knowledge of cloud-native architecture, microservices, and serverless computing
- Experience with CI/CD pipelines, automation, and DevOps principles, including familiarity with version control tools for ML models (e.g., DVC).
- Expertise in MLOps frameworks and tools (e.g., Kubeflow, MLflow, Airflow, TFX) for managing the end-to-end ML lifecycle, including model governance, compliance, and interpretability. Strong understanding of containerization (Docker) and orchestration (Kubernetes) for ML workloads.
- Proven ability to deploy machine learning models into production at scale using cloud-based platforms. Ability to optimize AI/ML models for cloud resource efficiency (e.g., tuning GPUs, TPUs, distributed training).
- Proficient in Python with strong experience in ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn). Familiarity with infrastructure automation tools (e.g., Terraform, Ansible, CloudFormation) and scripting languages (e.g., Bash, PowerShell).
- Excellent communication skills with the ability to convey complex technical concepts to both technical and non-technical audiences.