Platform Engineer,Model Shaping Job San Francisco area,California USA,Software Development

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

Benefits

Qualifications

Experienced with infrastructure automation tools (Terraform, Ansible), monitoring/observability stacks (Prometheus, Grafana), and CI/CD pipelines (Git Hub Actions, ArgoCD)
3+ years of experience in building infrastructure or backend components of production services
Skilled with analyzing non‑trivial issues of complex software systems and documenting your findings
Strong software engineering background in Python or Go
Strong communication skills, willing to document systems and processes and collaborate with peers of varying technical expertise
Have cloud environment (e.g., AWS/GCP/Azure) administration experience, preferably with a hybrid bare‑metal/cloud environment
Comfortable with the fundamentals of Linux environments and modern container/orchestration stacks (e.g., Docker and Kubernetes)
Developing large‑scale production systems with high reliability requirements
Pipeline orchestration frameworks (e.g., Kubeflow, Argo Workflows, Flyte)
Deployment of services for AI training or inference
Managing GPU workloads on HPC clusters, ideally with hands‑on experience in operating NVIDIA’s networking stack (e.g., NCCL, Mellanox firmware, GPUDirect RDMA)
Maintaining or contributing to open‑source projects

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Platform Engineer, Model Shaping