Senior Backend Engineer, Inference Platform
Company websitetogether.ai (Together AI, opens in new tab)
Base salary $200K to $290K
Employer-published annual base salary, USD. Advertised base range in San Francisco, CA
You apply on the employer's own site. Six Figure Work does not handle applications.
- LocationSan Francisco, CA
- WorkplaceWorkplace not stated
- Status at last checkSource accepting applications when checked
- Last checked (32 min ago) · observed since
About this job
About the Role
Together AI is building the Inference Platform that brings the most advanced generative AI models to the world. Our platform powers multi-tenant serverless workloads and dedicated endpoints, enabling developers, enterprises, and researchers to harness the latest LLMs, multimodal models, image, audio, video, and speech models at scale.
If you get a thrill from optimizing latency down to the last millisecond, this is your playground. You’ll work hands-on with tens of thousands of GPUs (H100s, H200s, GB200s, and beyond), figuring out how to fully utilize every FLOP and every gigabyte of memory.
You’ll collaborate directly with research teams to bring frontier models into production, making breakthroughs usable in the real world. Our team also works closely with the open source community, contributing to and leveraging projects like SGLang, vLLM, and NVIDIA Dynamo to push the boundaries of inference performance and efficiency.
- Shape the core inference backbone that powers Together AI’s frontier models.
- Solve performance-critical challenges in global request routing, load balancing, and large-scale resource allocation.
- Work with state-of-the-art accelerators (H100s, H200s, GB200s) at global scale.
- Partner with world-class researchers to bring new model architectures into production.
- Collaborate with and contribute to the open source community, shaping the tools that advance the industry.
- A culture of deep technical ownership and high impact — where your work makes models faster, cheaper, and more accessible.
- Competitive compensation, equity, and benefits.
Responsibilities
- Build and optimize global and local request routing, ensuring low-latency load balancing across data centers and model engine pods.
- Develop auto-scaling systems to dynamically allocate resources and meet strict SLOs across dozens of data centers.
- Design systems for multi-tenant traffic shaping, tuning both resource allocation and request handling — including smart rate limiting and regulation — to ensure fairness and consistent experience across all users.
- Engineer trade-offs between latency and throughput to serve diverse workloads efficiently.
- Optimize prefix caching to reduce model compute and speed up responses.
- Collaborate with ML researchers to bring new model architectures into production at scale.
- Continuously profile and analyze system-level performance to identify bottlenecks and implement optimizations.
Requirements
- 5+ years of demonstrated experience building large-scale, fault-tolerant, distributed systems and API microservices.
- Strong background in designing, analyzing, and improving efficiency, scalability, and stability of complex systems.
- Excellent understanding of low-level OS concepts: multi-threading, memory management, networking, and storage performance.
- Expert-level programming in one or more of: Rust, Go, Python, or TypeScript.
- Knowledge of modern LLMs and generative models and how they are served in production is a plus.
- Experience working with the open source ecosystem around inference is highly valuable; familiarity with SGLang, vLLM, or NVIDIA Dynamo will be especially handy.
- Experience with Kubernetes or container orchestration is a strong plus.
- Familiarity with GPU software stacks (CUDA, Triton, NCCL) and HPC technologies (InfiniBand, NVLink, MPI) is a plus.
- Bachelor’s or Master’s degree in Computer Science, Computer Engineering, or related field, or equivalent practical experience.
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 competitive benefits. The US base salary range for this full-time position is: $200,000 - $290,000 + equity + benefits. Our salary ranges are determined by location, level and role. Individual compensation will be determined by experience, skills, and job-related knowledge.
Application Policy
Please read each role carefully and apply to the position best suited to you. Candidates are limited to 6 applications within a 90-day period, and applications beyond that limit will be automatically rejected. You may apply to additional roles 90 days after your last application.
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
Source: Together AI on Greenhouse · View original posting (opens in new tab)
Pay in context
This role's base floor ($200,000) is above 71% of the 4,298 Software Engineering roles in California listed on this site; 146 others list the same floor. Their median floor is $176,000; the middle half runs from $149,100 to $202,000.
Only jobs on this site count, and each one publishes a base salary of $100,000 or more, so this compares six-figure jobs with each other, not with the whole market. Computed Nov 7, 2026.
This listingSenior Backend Engineer, Inference Platform$200K to $290K
Systems Research Engineer, GPU Programming$200K to $300K
Senior Software Engineer, Observability$200K to $280K
Platform Engineer, Model Shaping$200K to $290K
Machine Learning Engineer - Inference$200K to $300K
Research Engineer, Large-Scale Training$200K to $290K
Sr. Field Marketing & Community Manager$190K to $225K
Chart as a table
| Role | Published base |
|---|---|
| Senior Backend Engineer, Inference Platform (this listing) | $200K - $290K |
| Systems Research Engineer, GPU Programming | $200K - $300K |
| Senior Software Engineer, Observability | $200K - $280K |
| Platform Engineer, Model Shaping | $200K - $290K |
| Machine Learning Engineer - Inference | $200K - $300K |
| Research Engineer, Large-Scale Training | $200K - $290K |
| Sr. Field Marketing & Community Manager | $190K - $225K |
Observed changes
- First observed on the employer's board
- Began meeting the published-salary criteria
- Observed since
- Employer-stated posting date
- 2025-08-22
Where this pay comes from
Location as the employer wrote it: San Francisco
We offer competitive compensation, startup equity, health insurance and other competitive benefits. The US base salary range for this full-time position is: $200,000 - $290,000 + equity + benefits. Our salary ranges are determined by lo
- Method
- Employer text, read with fixed rules and re-verified
- Checked
- Rule set
- us-base-v2
The pay passage appears in the employer's own job text. Fixed, deterministic rules located it, and the passage below was checked against the stored copy of the posting.
What we verified
- The pay figures come from the employer's own listing, quoted exactly above.
- The pay is an annual base salary in US dollars with a minimum of at least $100,000.
- The role was publicly listed on the employer's job board when last checked.
We do not verify what the employer will actually offer, whether the employer is still recruiting for the role, or anything beyond what the employer published. Full methodology.
