Data Architect and Engineer
5 days ago
We are Intuitive.Cloud, a leading Cloud & SDx solution and services company that supports enterprise customers globally. Our engineering company delivers measurable value and key business outcomes.
Job OverviewWe are seeking an experienced Data Architect and Engineer to design and implement scalable AI microservices and robust data pipelines. This role requires a strong background in data engineering, expertise in building microservices architecture for AI/ML models, and deep understanding of CI/CD pipelines integrated with MLOps workflows.
Key Responsibilities- Ai As Microservices
- Design and develop Ai/ml models as microservices using frameworks such as FastApi, Flask, or Spring Boot.
- Implement APIs for Ai models to enable real-time and batch inferencing in scalable environments.
- Optimize Ai microservices for low latency, high availability, and scalability.
- Build and maintain robust data pipelines to support Ai/ml workflows, ensuring data availability, consistency, and security.
- Integrate structured and unstructured data from various sources into data lakes or warehouses.
- Develop ETL/ELT processes and automate data transformation workflows using tools like Apache Airflow, Databricks, or Spark.
- Develop Ci/cd pipelines to automate model training, testing, deployment, and monitoring using tools like Gitlab Actions, Jenkins, or Azure Devops.
- Implement Mlops practices to manage the lifecycle of Ai/ml models, including versioning, monitoring, and retraining workflows.
- Ensure seamless integration of data pipelines with Mlops systems for continuous learning and model improvement.
- Collaborate with DevOps teams to deploy Ai microservices in containerized environments using Docker and Kubernetes.
- Optimize deployment strategies for on-premise, cloud, or hybrid environments.
- Set up monitoring systems for data pipelines, Ai microservices, and model performance using tools like Prometheus, Grafana, or Datadog.
- Continuously improve system performance, reliability, and scalability.
- Experience: 7+ years of experience in data engineering or software development.
- At Least 3 Years Of Hands-On Experience In Deploying Ai/ml Models As Microservices.
- Proven Experience In Building Scalable Data Pipelines And Integrating Them With Mlops Workflows.
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