Support Engineer - Cloud (Australia)

March 9

Lambda

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Designing the world's most advanced GPU systems for Deep Learning.

Deep Learning • Machine Learning • Artificial Intelligence

51 - 200

💰 $39.7M Venture Round on 2022-11

Description

• Engage directly with customers to deeply understand their challenges, ensuring a personalized and effective support experience • Dive into complex software and hardware issues, providing timely and efficient solutions • Craft comprehensive documentation of solutions and contribute to enhancing support procedures, ensuring continuous improvement in service quality • Identify common customer pain points and collaborate closely with engineering teams to develop innovative solutions, constantly improving the overall customer experience • Collaborate in the development of new products, contributing your expertise to shape the future of deep learning cloud infrastructure

Requirements

• Proven experience in clustered or HPC environments, showcasing your mastery in Linux administration • Proficiency in Bash or Python scripting, enabling you to automate tasks and streamline operations • Excellent written and oral communication skills, ensuring effective interaction with both technical and non-technical stakeholders • Hands-on experience in private or hybrid cloud environments, such as Azure, GCP, AWS, OCI, or OpenStack • Proven professional experience administering Kubernetes clusters Nice to Have: • Familiarity with infrastructure-as-code tools (Terraform, Puppet, Ansible, Chef, etc.) • Experience with high throughput networking technologies, RDMA, NCCL, GPUDirect, SLURM, or distributed GPU training systems • Experience with ML/AI/deep learning and a solid understanding of the hardware, software, and tools used in this domain • Experience with NVIDIA data center GPUs and distributed or parallel file systems

Benefits

• Health, dental, and vision coverage for you and your dependents • Commuter/Work from home stipends • 401k Plan with 2% company match • Flexible Paid Time Off Plan that we all actually use