LLM Inference Frameworks and Optimization Engineer
Together AI
LLM Inference Frameworks and Optimization Engineer at Together AI is a full time role based in San Francisco, Singapore, United States. It was published on 25 March 2025 and was open at last check.
| Role | LLM Inference Frameworks and Optimization Engineer |
|---|---|
| Company | Together AI |
| Location | San Francisco, Singapore, United States |
| Employment type | Full Time |
| Published | 25 March 2025 |
| Status | Open at last check |
About the Role
At Together.ai, we are building state-of-the-art infrastructure to enable efficient and scalable inference for large language models (LLMs). Our mission is to optimize inference frameworks, algorithms, and infrastructure, pushing the boundaries of performance, scalability, and cost-efficiency.
We are seeking an Inference Frameworks and Optimization Engineer to design, develop, and optimize distributed inference engines that support multimodal and language models at scale. This role will focus on low-latency, high-throughput inference, GPU/accelerator optimizations, and software-hardware co-design, ensuring efficient large-scale deployment of LLMs and vision models.
This role offers a unique opportunity to shape the future of LLM inference infrastructure, ensuring scalable, high-performance AI deployment across a diverse range of applications. If you're passionate about pushing the boundaries of AI inference, we’d love to hear from you!
Responsibilities
Inference Framework Development and Optimization
- Design and develop fault-tolerant, high-concurrency distributed inference engine for text, image, and multimodal generation models.
- Implement and optimize distributed inference strategies, including Mixture of Experts (MoE) parallelism, tensor parallelism, pipeline parallelism for high-performance serving.
- Apply CUDA graph optimizations, TensorRT/TRT-LLM graph optimizations, and PyTorch-based compilation (torch.compile), and speculative decoding to enhance efficiency and scalability.
Software-Hardware Co-Design and AI Infrastructure
- Collaborate with hardware teams on performance bottleneck analysis, co-optimize inference performance for GPUs, TPUs, or custom accelerators.
- Work closely with AI researchers and infrastructure engineers to develop efficient model execution plans and optimize E2E model serving pipelines.
Requirements
Must-Have:
- Experience:
- 3+ years of experience in deep learning inference frameworks, distributed systems, or high-performance computing.
- Technical Skills:
- Familiar with at least one LLM inference frameworks (e.g., TensorRT-LLM, vLLM, SGLang, TGI(Text Generation Inference)).
- Background knowledge and experience in at least one of the following: GPU programming (CUDA/Triton/TensorRT), compiler, model quantization, and GPU cluster scheduling.
- Deep understanding of KV cache systems like Mooncake , PagedAttention , or custom in-house variants.
- Programming:
- Proficient in Python and C++/CUDA for high-performance deep learning inference.
- Optimization Techniques:
- Deep understanding of Transformer architectures and LLM/VLM/Diffusion model optimization.
- Knowledge of inference optimization, such as workload scheduling, CUDA graph, compiled, efficient kernels
- Soft Skills:
- Strong analytical problem-solving skills with a performance-driven mindset.
- Excellent collaboration and communication skills across teams.
Nice-to-Have:
- Experience in developing software systems for large-scale data center networks with RDMA/RoCE
- Familiar with distributed filesystem(e.g., 3FS, HDFS, Ceph)
- Familiar with open source distributed scheduling/orchestration frameworks, such as Kubernetes (K8S)
- Contributions to open-source deep learning inference 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 advancement such as FlashAttention, Hyena, FlexGen, and RedPajama. 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 competitive benefits. The US base salary range for this full-time position is: $160,000 - $230,000 + 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
Create your free OnJob profile to apply — we'll take you to Together AI's application after sign-up. · Posted 25 Mar 2025.
LLM Inference Frameworks and Optimization Engineer at Together AI — questions answered
What does the LLM Inference Frameworks and Optimization Engineer role at Together AI pay?
Together AI does not publish a salary on this LLM Inference Frameworks and Optimization Engineer listing, so OnJob shows no figure for it rather than an estimate. For what this role pays across the market, the OnJob salary guides aggregate the live listings that do disclose pay.
Where is the LLM Inference Frameworks and Optimization Engineer role at Together AI based?
Together AI lists this LLM Inference Frameworks and Optimization Engineer role in San Francisco, Singapore, United States, advertised as full time work at that location. Larger employers sometimes cover several sites under one city name, so confirm the exact office with Together AI before you apply.
Is the LLM Inference Frameworks and Optimization Engineer role at Together AI still open?
The LLM Inference Frameworks and Optimization Engineer posting at Together AI was open at OnJob's last check of the employer's careers page, having been published on 25 March 2025. OnJob re-checks source listings on each build and marks a role closed once it disappears, but listings can close without notice, so the employer's own page is the final word.
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