Principal Software Engineer to work on cutting-edge AI/ML applications and agent systems, leveraging modern inference platforms to build production-ready prototypes.
You will contribute to upstream communities like vLLM, TGI, PyTorch, and OpenVINO while building innovative applications that demonstrate the capabilities of next-generation AI/ML systems.
The ideal candidate is energized by working concurrently on a wide variety of projects, independently as well as within a team environment.
What you will do: Build high-quality, high-performing AI/ML applications and agent systems using modern inference platforms for multi-modal and distributed model serving Apply and optimize inference techniques including KV cache management, model quantization, and distributed serving to production workloads Contribute to upstream inference runtime communities such as vLLM, TGI, PyTorch, OpenVINO, and related projects Build multi-modal AI applications integrating vision, language, and other modalities Provide technical leadership and coordination across multiple stakeholders and engineering teams Apply a growth mindset by staying current with rapid advancements in AI/ML inference technologies Benchmark and analyze inference performance at scale, driving data-driven optimization decisions Publicize innovations through blogs, presentations, conferences, and other technical venues What you will bring: Bachelor's degree in Computer Science, Engineering, or equivalent experience 5+ years of experience in AI/ML engineering with focus on production inference systems Deep expertise in PyTorch and modern deep learning frameworks Hands-on experience with inference runtime optimization (model serving, batching, KV cache management) Advanced programming skills in Python and C++ Proven ability to contribute to and lead open source projects Strong self-motivation and organizational skills Ability to work concurrently on multiple projects, independently and within a team environment Excellent English written and verbal communication skills Collaborative attitude and willingness to share ideas openly The following are considered a plus: Experience with vLLM, TGI (Text Generation Inference), or similar inference runtimes Contributions to PyTorch, OpenVINO, or other inference frameworks Experience with distributed model serving and GPU optimization Familiarity with Kubernetes and cloud-native AI/ML deployments Knowledge of model quantization techniques (GPTQ, AWQ, FP8, etc.) Experience with CUDA, Triton, or other GPU programming frameworks Experience with diffusion models and diffusion transformers Experience building AI agents and agentic systems About Red Hat is the world's leading provider of enterprise software solutions, using a community-powered approach to deliver high-performing Linux, cloud, container, and Kubernetes technologies.
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