over 1 year ago
Remote, WorldwideSenior
Responsibilities
- Deploy scalable, production-ready ML services with optimized infrastructure.
- Optimize GPU resources using MIG and NOS.
- Manage cloud storage to ensure high availability and performance.
- Integrate state-of-the-art ML techniques into workflows.
- Develop Retrieval-Augmented Generation systems integrating various processors.
- Set up monitoring and logging solutions using various tools.
- Write and maintain CI/CD pipelines for seamless deployment processes.
- Create Helm templates for rapid Kubernetes node deployment.
- Automate workflows using cron jobs and Airflow DAGs.
Requirements
- Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
- Proficiency in Kubernetes, Helm, and containerization technologies.
- Experience with GPU optimization and cloud platforms.
- Strong knowledge of monitoring tools and scripting languages.
- Hands-on experience with CI/CD tools and workflow management systems.
- Familiarity with model serving and optimization technologies.
Benefits
- Engage in meaningful AI research with a focus on decentralized inference and multi-agent systems.
- Build scalable and sustainable AI systems that reduce reliance on massive compute clusters.
- Collaborate with a highly technical team of experienced engineers and researchers.