TensorRT Jobs
3 open roles mentioning TensorRT
LLM Inference Frameworks and Optimization Engineer
Together AI
Together.ai is building state-of-the-art infrastructure for efficient and scalable inference of large language models (LLMs). The company's mission is to optimize inference frameworks, algorithms, and infrastructure to push the boundaries of performance, scalability, and cost-efficiency. They are seeking an Inference Frameworks and Optimization Engineer to design, develop, and optimize distributed inference engines for 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 position offers a unique opportunity to shape the future of LLM inference infrastructure and ensure scalable, high-performance AI deployment across diverse applications.
$160k - $230k
AI Researcher, Core ML (Turbo)
Together AI
The Turbo team operates at the intersection of efficient inference (algorithms, architectures, engines) and post-training/RL systems. We are responsible for building and managing the systems that power Together's API, focusing on high-performance inference and RL/post-training engines capable of operating at production scale. Our core mission is to advance the frontiers of efficient inference and RL-driven training, aiming to make models significantly faster and more cost-effective to run, while simultaneously enhancing their capabilities through RL-based post-training methods. This role involves working across the entire stack, from RL algorithms and training engines to kernels and serving systems, to develop and refine state-of-the-art models using RL pipelines. We value individuals with deep expertise in one area and a strong willingness to collaborate and grow across others.
$200k - $280k
Generative AI Inference Engineer
Stability AI
We are seeking passionate Machine Learning Engineers to join our Inference team, focusing on the creative applications of generative AI models. The ideal candidate will have substantial experience developing and running inference for multi-modal models. A deep understanding of diffusion model architectures and familiarity with workflow tools like ComfyUI are a big plus. You will be expected to leverage and push the boundaries of state-of-the-art inference optimization techniques for multi-modal generative models. This role offers the opportunity to work alongside top researchers and engineers, utilizing cutting-edge high-performance computing resources to make a significant impact in the rapidly evolving field of generative AI.