Senior Backend Engineer, Inference Platform

Together AI

San Francisco (CA)

On-site

USD 160,000 - 250,000

Full time

14 days+

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Benefits offered by this job

Competitive compensation
Startup equity
Health insurance

Job summary

Together AI is searching for a skilled engineer to join their team, focusing on building and optimizing a large-scale inference platform. This role involves developing low-latency systems and collaborating with research teams to deploy advanced AI models. Candidates should have at least 5 years of experience in distributed systems and a strong programming background in languages such as Rust, Go, Python, or TypeScript. The position offers a competitive salary of $160,000 to $250,000 plus equity and benefits.

Qualifications

  • 5+ years of experience in building large-scale, fault-tolerant systems.
  • Strong background in designing efficient, scalable systems.
  • Excellent understanding of multi-threading and memory management.

Responsibilities

  • Build and optimize global and local request routing.
  • Develop auto-scaling systems to allocate resources.
  • Design systems for multi-tenant traffic shaping.

Skills

Building large-scale distributed systems
API microservices
Low-level OS concepts
Programming in Rust
Programming in Go
Programming in Python
Programming in TypeScript
Kubernetes
GPU software stacks
HPC technologies

Education

Bachelor’s or Master’s degree in Computer Science

Job description

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.

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 a 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 a related field, or equivalent practical experience.
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 advancement such as FlashAttention, Hyena, FlexGen, and RedPajama. We invite you to join a passionate group of researchers and engineers in our journey in building the next generation AI infrastructure.

Compensation

We offer competitive compensation, startup equity, health insurance and other competitive benefits. The US base salary range for this full‑time position is: $160,000 – $250,000 + equity + benefits. Our salary ranges are determined by location, level and role. Individual compensation will be determined by experience, skills, and job‑related knowledge.

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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