Staff Cloud Software Engineer, Tenstorrent

• 10+ years of hands-on software engineering experience working with distributed systems in Cloud and/or HPC environments
• 5+ years of experience working with clustered (multi-host) AI hardware and applications for training and inference
• 5+ years of experience with Kubernetes clusters, including cluster and application deployment (e.g., CNI, CSI, Helm), operations, and development of extensions (e.g., Device plugins, Operators)
• Strong working knowledge of Python and Go
• Infrastructure as Code as a first-class citizen (e.g. Ansible)
• Strong Git, GitOps, and CI/CD experience
• Familiarity with performance requirement implications of AI/ML workloads, both inference and training
• Familiarity with virtualization technologies and platforms
• Hands-on experience with MLOps concepts and frameworks for end-to-end model training pipelines
• Strong understanding of networking concepts – experience with network hardware configuration and management is a plus
• Familiarity with security implications of multi-tenant environments on hardware, software, and networking level
• Familiarity with observability, monitoring and alerting tools (e.g., Grafana, Prometheus, Loki)
• Agile / lean software project management experience
• Strong programming skills with years of experience in various programming languages; familiarity of both object oriented and functional programming
• REST API development and integration experience – full-stack web development experience is a plus

• This Staff Cloud Software position is looking to bring new specialized expertise into the team in the area of distributed high-performance and AI computing, especially in Kubernetes-based cloud native environments
• You will be driving design, implementation, and integration of systems to support scaling compute capabilities seamlessly from single-host systems into exaflop-scale clusters
• Design and drive implementation of distributed systems for AI computing applications in Cloud and novel supercomputing cluster environments
• Hands-on software development, testing, integration, operations, and support
• Closely collaborate with the team through the full stack and life cycle of AI data center applications, from data center design and rollout to MLOps
• Operate within on-premises data centers and public cloud environments
• Drive projects through their whole software development lifecycle, both on technical and non-technical side
• Collaboration with both highly technical and non-technical stakeholders with differing backgrounds, being able to communicate highly complex topics to diverse audiences
• Continuous improvement of engineering practices through code reviews and adoption of relevant techniques and technologies

Total funding: $1.3bn

Advances in artificial intelligence apps, combined with a global chip shortage, are strong tailwinds for chip processor Tenstorrent. The semi-conducter developer is designing specialized chips for running artificial intelligence applications, building chips for what it calls "software 2.0".