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Platform Engineer, Model Shaping

Together AI · Remote

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MeritLog keeps this source-backed description for reference. Availability is not verified, and there is no application link here.

Last seen by MeritLog September 10, 2026Source: GreenhouseSource version: greenhouse-job-board-v1

Source: the employer's Greenhouse job board. Open the original listing for current details. Availability is not verified for this retained page.

Job details

Work model
Remote
Salary
Conflicting source ranges
Location
San Francisco
Occupation
Computer Systems Engineers/Architects(O*NET 15-1299.08)

What the role asks for

What you'd do

  • 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 datacenters, supporting a highly heterogeneous hardware landscape
  • Partner with teams developing internal services, co-designing these services and incorporating them in systems built within Together

What they're asking for

  • 3+ years of experience in building infrastructure or backend components of production servicesExperience
  • Extensive experience designing, operating, and troubleshooting production Linux environments and Kubernetes-based platformsSkill
  • Strong software engineering background in Python or GoSkill
  • Experienced with infrastructure automation tools (Terraform, Ansible), monitoring/observability stacks (Prometheus, Grafana), and CI/CD pipelines (GitHub Actions, ArgoCD)Skill
  • Cloud environment (e.g., AWS/GCP/Azure) administration experience, preferably with a hybrid bare-metal/cloud environmentSkill
  • Strong communication skills, be willing to document systems and processes and collaborate with peers of varying technical expertiseSkill
  • Comfortable operating across the stack, from cluster operations and infrastructure automation to backend service developmentSkill
  • Developing large-scale production systems with high reliability requirementsSkill
  • Pipeline orchestration frameworks (e.g., Kubeflow, Argo Workflows, Flyte)Skill
  • Managing GPU workloads on HPC clusters, ideally with hands-on experience in operating NVIDIA’s networking stack (e.g., NCCL, Mellanox firmware, GPUDirect RDMA)SkillPreferred
  • Deployment of services for AI training or inferenceSkill
  • Networking fundamentals, including TCP/IP, DNS, routing, load balancing, TLS, and network debugging toolsSkill
  • Maintaining or contributing to open-source projectsSkill

Parsed by MeritLog from the employer’s own posting. The full description follows below.

Job description

About the Role The Model Shaping team at Together AI works on products and research for tailoring open foundation models to downstream applications. We build services that allow machine learning developers to choose the best models for their tasks and further improve these models using domain-specific data. In addition to that, we develop new methods for more efficient model training and evaluation, drawing inspiration from a broad spectrum of ideas across machine learning, natural language processing, and ML systems. As a Platform Engineer in Model Shaping, you will work at the intersection of backend engineering and infrastructure, building the foundational layers of Together’s platform for model customization and evaluation. You will design, develop, and operate both the backend services and the underlying systems that enable us to sustainably and reliably scale 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. Responsibilities • 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 datacenters, supporting a highly heterogeneous hardware landscape • Partner with teams developing internal services, co-designing these services and incorporating them in systems built within Together Requirements • 3+ years of experience in building infrastructure or backend components of production services • Extensive experience designing, operating, and troubleshooting production Linux environments and Kubernetes-based platforms • 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) • Cloud environment (e.g., AWS/GCP/Azure) administration experience, preferably with a hybrid bare-metal/cloud environment • Strong communication skills, be willing to document systems and processes and collaborate with peers of varying technical expertise • Comfortable operating across the stack, from cluster operations and infrastructure automation to backend service development Experience in any of the following will make you stand out: • Developing large-scale production systems with high reliability requirements • Pipeline orchestration frameworks (e.g., Kubeflow, Argo Workflows, Flyte) • Managing GPU workloads on HPC clusters, ideally with hands-on experience in operating NVIDIA’s networking stack (e.g., NCCL, Mellanox firmware, GPUDirect RDMA) • Deployment of services for AI training or inference • Networking fundamentals, including TCP/IP, DNS, routing, load balancing, TLS, and network debugging tools • Maintaining or contributing to open-source projects About Together AI Together AI, the AI Native Cloud, is purpose-built for AI engineers. AI application developers get high-performance inference that scales reliably, fine-tuning and reinforcement learning for creating frontier-level specialized models, and pre-training at massive scale for fully custom intelligence, all around a marketplace of leading open models that teams can run, adapt, and own. Trusted by Cursor, Decagon, ElevenLabs, Salesforce, and Zoom, Together serves 400+ trillion tokens a month. Compensation We offer competitive compensation, startup equity, health insurance, and other benefits, as well as flexibility in terms of remote work. The US base salary range for this full-time position is $200,000 - $290,000. Our salary ranges are determined by location, level and role. Individual compensation will be determined by experience, skills, and job-related knowledge. Equal Opportunity Together AI is an Equal Opportunity Employer and is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and more. Please see our privacy policy at https://www.together.ai/privacy

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