Platform Engineer, Model Shaping

Together AI is hiring a Platform Engineer, Model Shaping in San Francisco, United States. It pays $200k-$290k a year and Level rates it ; you can apply on Together AI.

Level's read on this job

On Level's scale, this role is Builds AI ●●●●: the job is building AI systems.
The posting mentions Cursor, Elevenlabs and Decagon among its tools and skills.
Level classes it as a mid-level role.
Together AI has 83 other open roles on Level.

AI in this role

cursorelevenlabsdecagon

fine-tuningnlp

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

How we rate this

Platform Engineer, Model Shaping at Together AI rates 97 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Key facts

Platform Engineer, Model Shaping is an open job at Together AI.
Level rates this role AI Level 4 of 4: Builds AI.
The listed salary is $200k-$290k a year.
The role is based in San Francisco.
The job was posted on July 16, 2025.
Seniority: mid.
Applications are handled by Together AI. Apply on Together AI

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

Fine-tuningNLPCursorElevenlabsDecagon

Questions you could be asked

Walk me through fine-tuning a model: what data did you use, and how did you check the result?
What NLP problem have you worked on, and how did you measure whether it actually worked?
What are the limits of Cursor that you've run into, and how did you work around them?
What's a project where you used Elevenlabs hands-on?
Walk me through how you've used Decagon in your day-to-day work.

Adapt your resume

List these exact terms on your resume: Fine-tuning, NLP, Cursor, Elevenlabs, and Decagon. An applicant tracking system matches the wording, not the idea.
Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.

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