This role has closed. Together AI has taken the posting down.
hirly last saw it live on 6 September 2026. See similar open roles below, or browse all jobs in San Francisco.
Together AI
LLM Inference Frameworks and Optimization Engineer
San Francisco, Singapore, Amsterdam
Similar open jobs
- 3D Print Optimization EngineerFormlabs · Boston, MAFirst seen todayremote
- 3D Print Optimization EngineerFormlabs · Somerville, MAFirst seen todayremote
- Artificial Intelligence and Optimization EngineerBah · Honolulu, HIFirst seen yesterday
- Experienced Deep Learning Optimization Engineer- Compilers TeamMobileye · Haifa, IsraelFirst seen yesterday
- ML Runtime Optimization EngineerApplied Intuition · SunnyvaleFirst seen yesterday
- Radar Optimization EngineerLeidos · 6314 Remote/Teleworker USFirst seen 2d agoremote
- Radar Optimization EngineerLeidos · 6314 Remote/Teleworker USFirst seen 2d agoremote
- Completions Optimization EngineerNOV · Kochi, Kerala, IndiaFirst seen 2d ago
- Completions Optimization EngineerNOV · Conroe, TX, United StatesFirst seen 2d ago
- Material Cost Optimization EngineerFord Global · Bangkok, ThailandFirst seen 2d ago
- SoC Power Analysis and Optimization Engineer, Graviton TeamAmazon · Haifa, Haifa, ISR; Tel Aviv-Yafo, Tel Aviv, ISRFirst seen 2d ago
- ML and Optimization EngineerNrel · 2 LocationsFirst seen 2d ago
- AI Optimization EngineerOxy · Houston, TexasFirst seen 2d ago
- OMT RAM RDA Process Optimization EngineerMicron · Taichung - Fab 16, TaiwanFirst seen 2d ago
- Software Enabling and Optimization EngineerIntel · India, BangaloreFirst seen 2d ago
hirly's read of this role
- Seniority
- Mid level
- Stated salary
- $160,000 – $230,000 per year
- Country
- SG
- Work mode
- Remote-friendly
- First seen by hirly
- 2 Sept 2026
Derived automatically from the posting.
the posting
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