- Location
- San Francisco
- Level
- Mid level
- Posted
- 6 days ago
About this role
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 is a research-driven artificial intelligence company. We believe open and transparent AI systems will drive innovation and create the best outcomes for society, and together we are on a mission to significantly lower the cost of modern AI systems by co-designing software, hardware, algorithms, and models. We have contributed to leading open-source research, models, and datasets to advance the frontier of AI, and our team has been behind technological advancements such as FlashAttention, RedPajama, SWARM Parallelism, and SpecExec. We invite you to join a passionate group of researchers in our journey in building the next generation AI infrastructure.
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
As published by Together AI. Applications are handled on their site.
Skills this posting mentions
About Together AI
Together AI is the AI Native Cloud, purpose-built for AI engineers and researchers with a full suite of tooling across inference, model shaping, and pre-training. AI natives can use Together AI as a full-stack AI platform - from a high- performance inference engine built for reliable and fast scaling to on-demand GPU clusters and massive-scale AI factories. Together AI continuously pushes the frontier forward by productizing cutting-edge research from our world-leading AI systems research team. By combining research velocity with production-grade infrastructure, we enable companies to reliably scale AI-native applications as fast as the field evolves. Trusted by leading AI natives like Cursor, Decagon, Eleven Labs, AI21, Hedra, and Cartesia, as well as SaaS innovators such as Salesforce, Zoom, and Zomato, Together AI powers the next generation of AI-native applications.
All 65 openings at Together AIOne click, then it is written
Apply to Together AI with a resume written for this role.
Queue Platform Engineer, Model Shaping and I read the posting, rewrite your resume against it, draft the cover letter, and score the fit. Then you press send, or press one button and I fill in Together AI’s form for you.
01Drop your resume
A PDF or a LinkedIn URL. About a minute, once.
02I rank the openings
Every weekday morning, the live catalog scored against your history. Up to 20 worth your time, not two hundred links.
03Each one is written up
Resume rewritten for the posting, a cover letter, a fit score. Press send, or let me fill in the form.
- 25 sent a week, free
- No card
- Nothing sent until you say so
More roles at Together AI
See all- Today
- Today
- 3 days ago
- 4 days ago
Staff Engineer, Distributed Storage and HPC & AI Infrastructure
Bangalore IndiaRemote
2 locationsStaffEngineering - 4 days ago
- 4 days ago
Similar roles elsewhere
See morePut this to work
Paste your career in once. Every application after that is written for you.
Drop a resume or a LinkedIn URL. I rank the live openings against it, rewrite the resume and write a cover letter for the best of them, and fill in the employer's form when you press the button. You read, you decide what goes out.
01Drop your resume
A PDF or a LinkedIn URL. About a minute, once.
02I rank the openings
Every weekday morning, the live catalog scored against your history. Up to 20 worth your time, not two hundred links.
03Each one is written up
Resume rewritten for the posting, a cover letter, a fit score. Press send, or let me fill in the form.
- New matches ranked and written before you are up.
- Every bullet stays inside what your history supports. Nothing invented.
- Queued, submitted, interviewing, offer: one screen, not a spreadsheet.
500 free credits on sign-up. No card. Nothing is sent until you say so.
Listed from the job board Together AI publishes. Refolk is not the employer and does not handle their hiring. Applications go to Together AI directly.