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Are you passionate about computer graphics and high-performance computing? Would you like to have hands-on experience with state-of-the-art HW, sometimes even before others get a chance?We are looking for an experienced ML Ops Engineer or Dev Ops to contribute to deploy, maintain, and develop automation and infrastructure systems for major hardware vendor.The ideal candidate should have a background in ML operations, proficient in collaboration with Data Engineering teams, and is well versed with automation tools on clustered deployments. Responsibilities: Your responsibilities will be focused around supporting local Data Engineering, Software Infrastructure and Research teams:- Build tailored automation systems for teams of ML developers,- Facilitate collaboration between Data Engineering, ML Research and Software Infrastructure teams,- Implement new helper tools, focusing on practical deployment and cost/resource management. Skills: - Decent understanding of Unix/Linux,- Decently experienced in either Slurm or Kubernetes (both preferred; should be able to setup, configure, manage and expand the clusters as needed),- Can work with Bash, JS and Python with at least good experience in one of them,- Experienced with GraphQL and Rest API (throttling, caching, on client side using redis, custom solutions etc.),- Experienced with Ansible, Terraform or Pulumi, Docker, Helm. Nice to have: - Experience with ML Frameworks,- Technical academin degree in IT or related,- General MLOPs pipeline expertise.
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