Apply📍 India
🧭 Full-Time
🔍 3D visualization and generative AI
- 3+ years of total experience in DevOps with relevant experience in implementing MLOps solutions.
- Experience with Google Cloud, deploying machine learning models in production environments.
- Extensive experience with containerization technologies like Docker and orchestration tools like Kubernetes.
- Proficiency in Infrastructure as Code (IaC) for provisioning and configuration of cloud resources.
- Experience with DevOps practices and tools including CI/CD, version control, and automated testing.
- Excellent problem-solving skills to troubleshoot MLOps workflows.
- Good to have: experience in deployment of diffusion models, LLM Models, Generative AI products.
- Certifications in cloud platforms such as AWS and Google Cloud are beneficial.
- Experience with MLOps tools/frameworks like Kubeflow, MLflow, TFX.
- Knowledge of data engineering principles and software development methodologies (e.g., Agile, Scrum).
- Lead the design and implementation of DevOps and MLOps solutions to enhance our platform's capabilities.
- Define and set development, testing, release, update, and support processes for DevOps and MLOps operations.
- Deploy diffusion models, LLM Models, and cost-effective deployment of Generative AI products.
- Collaborate closely with data scientists, machine learning engineers, and product developers.
- Develop and implement end-to-end CI/CD pipelines specifically tailored for Generative AI model workflows.
- Optimize infrastructure for performance, scalability, and cost efficiency in machine learning applications.
- Stay updated with MLOps tools and trends for continuous improvement.
- Provide technical leadership and mentorship to junior team members.
DockerLeadershipAgileKubeflowKubernetesMachine LearningMLFlowSCRUMData engineeringCI/CDDevOps
Posted 3 months ago
Apply