Platform Engineer, Together AI

• 3+ years of experience in building infrastructure or backend components of production services
• Comfortable with the fundamentals of Linux environments and modern container/orchestration stacks (e.g., Docker and Kubernetes)
• Strong software engineering background in Python or Go
• Experienced with infrastructure automation tools (Terraform, Ansible), monitoring/observability stacks (Prometheus, Grafana), and CI/CD pipelines (GitHub Actions, ArgoCD)
• Skilled with analyzing non-trivial issues of complex software systems and documenting your findings
• Have cloud environment (e.g., AWS/GCP/Azure) administration experience, preferably with a hybrid bare-metal/cloud environment
• Strong communication skills, willing to document systems and processes and collaborate with peers of varying technical expertise

Desirable

• As a Platform Engineer at Model Shaping, you will work on the foundational layers of Together’s platform for model customization and evaluation
• You will design the infrastructure and backend services that will allow us to sustainably and reliably scale the systems powering production workflows launched by our users, as well as internal research experiments
• You will operate in a cross-functional environment, collaborating with other engineers and researchers in the team to improve the infrastructure based on the needs of projects they work on
• You will also interact with other engineering teams at Together (such as Commerce, Data Engineering, and Cloud Infrastructure) to integrate the services developed by Model Shaping with systems developed by those teams
• Design and build Together’s systems and infrastructure for model customization, including user-facing features and internal improvements
• Contribute to reliability improvements for the platform, participating in an on-call rotation and improving processes for incident response
• Create and improve internal tooling for deployment, continuous integration, and observability
• Build a job orchestration platform spanning multiple data centers, supporting a highly heterogeneous hardware landscape
• Partner with teams developing internal services, co-designing these services and incorporating them in systems built by Model Shaping