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Mempage Technologies

3 months ago

Hyderabad, India Mempage Full time

Responsibilities :

- Collaborate with data scientists and ML engineers to understand machine learning models and their deployment requirements.

- Design and implement MLOps pipelines on GCP for efficient training, validation, deployment, and monitoring of ML models.

- Utilize GCP services like AI Platform Training, Vertex AI Pipelines, and Cloud Functions to automate ML workflows.

- Configure and manage cloud infrastructure resources (Compute Engine, Kubernetes Engine) for ML model training and deployment.

- Integrate MLOps pipelines with CI/CD workflows for seamless deployment and continuous delivery of ML models.

- Monitor and maintain deployed ML models, ensuring high availability, performance, and cost-effectiveness.

- Implement automated data validation and model monitoring to detect potential issues and data drift.

- Troubleshoot and debug issues related to ML pipelines and deployed models.

- Stay up-to-date with the latest advancements in GCP MLOps tools and best practices.

- Document MLOps pipelines and procedures for clear communication and collaboration.

Required Skills :

- 4+ years of experience in software development or related field.

- Strong understanding of machine learning concepts and their application in real-world scenarios.

- Proven experience with DevOps principles and tools (CI/CD pipelines, version control).

- Expertise in Python programming with libraries like NumPy, Pandas, and familiarity with machine learning frameworks (Scikit-learn, TensorFlow, PyTorch) is a plus.

- Solid understanding of cloud computing concepts and experience with GCP is preferred.

- Experience with GCP services like AI Platform, Vertex AI, Cloud Storage, and Cloud Monitoring.

- Experience with containerization technologies (Docker, Kubernetes) is a plus.

- Excellent analytical and problem-solving skills.

- Strong communication and collaboration skills.

- Ability to work independently and manage multiple projects effectively.

Desired Skills :

- Experience with model deployment frameworks like Kubeflow or MLflow.

- Experience with infrastructure as code tools (Terraform) for managing GCP resources.

- Experience with monitoring and logging tools for ML pipelines (Stackdriver Logging, Prometheus).

- Familiarity with Explainable AI (XAI) techniques is a plus

(ref:hirist.tech)