Senior Performance and Scale Engineer - Distributed LLM Inference at Red River

Raanana, Center District, Spain -

Full Time

Start Date

Immediate

Expiry Date

14 Feb, 26

Salary

0.0

Posted On

16 Nov, 25

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Performance Engineering, Systems-Level Software Design, Kubernetes, OpenShift, AI Fundamentals, Large Language Models, Python, Bash, Linux, Data Analysis, Visualization, DevOps, Performance Benchmarking, Automation, Community Leadership, Performance Observability

Industry

IT Services and IT Consulting

Description

Job Summary The Red Hat Performance and Scale Engineering team is looking for a Senior Performance Engineer to join us in the PSAP (Performance and Scale for AI Platforms) team, driving the performance and scalability of distributed inference for Large Language Models (LLMs) Serving modern LLMs for production inference requires distributing the model, the computation, and the requests across numerous specialized hardware accelerators across multiple nodes. This introduces complex performance challenges, from optimizing inter-GPU and inter node communication and kernel execution to minimizing latency under concurrent loads. You will be responsible for characterizing, modeling, and enhancing the performance of these distributed systems, ensuring that Red Hat's AI platforms offer industry-leading throughput, latency, and cost-efficiency. This role needs a seasoned engineer that thinks creatively, adapts to rapid change, and has the willingness to learn and apply new technologies. You will be joining a vibrant open source culture, and helping promote performance and innovation in this Red Hat engineering team. The border mission of the Performance and Scale team is to establish performance and scale leadership of the Red Hat product and cloud services portfolio. The scope includes component level, system and solution analysis and targeted enhancements. The team collaborates with engineering, product management, product marketing and customer support as well as Red Hat’s hardware and software ecosystem partners. At Red Hat, our commitment to open source innovation extends beyond our products - it’s embedded in how we work and grow. Red Hatters embrace change – especially in our fast-moving technological landscape – and have a strong growth mindset. That's why we encourage our teams to proactively, thoughtfully, and ethically use AI to simplify their workflows, cut complexity, and boost efficiency. This empowers our associates to focus on higher-impact work, creating smart, more innovative solutions that solve our customers' most pressing challenges. What you will do: Define and track key performance indicators (KPIs) and service level objectives (SLOs) for large-scale, distributed LLM inference services in Kubernetes/OpenShift Participate in the performance roadmap for distributed inference, including multi-node and multi-GPU scaling studies, interconnect performance analysis, and competitive benchmarking Formulate performance test plans and execute performance benchmarks to characterize performance, drive improvements, and detect performance issues through data analysis and visualization Develop and maintain tools, scripts, and automated solutions that streamline performance benchmarking tasks. Collaborate with cross-functional engineering teams to identify and address performance issues. Partner with DevOps to bake performance gates into GitHub Actions/OpenShift Pipelines. Explore and experiment with emerging AI technologies relevant to software development, proactively identifying opportunities to incorporate new AI capabilities into existing workflows and tooling. Triage field and customer escalations related to performance; distill findings into upstream issues and product backlog items. Publish results, recommendations, and best practices through internal reports, presentations, external blogs, and official documentation. Represent the team at internal and external conferences, presenting key findings and strategies. What you will bring: 3+ years in performance engineering or systems‑level software design Hands‑on expertise with Kubernetes/OpenShift Basic understanding of AI and LLMs fundamentals Fluency in Python (data & ML), strong Bash/Linux skills Exceptional communication skills - able to translate raw performance numbers into customer value and executive narratives Commitment to open‑source values The following is considered a plus: Master’s or PhD in Computer Science, AI, or a related field History of upstream contributions and community leadership Hands-on experience with Kubernetes/OpenShift Familiarity with performance observability stacks such as perf/eBPF‑tools, Nsight Systems, PyTorch Profiler, among others Hands-on experience with modern LLM inference server stack (e.g., vLLM, TensorRT-LLM, TGI, Triton Inference Server). #LI-OA1 About Red Hat Red Hat is the world’s leading provider of enterprise open source software solutions, using a community-powered approach to deliver high-performing Linux, cloud, container, and Kubernetes technologies. Spread across 40+ countries, our associates work flexibly across work environments, from in-office, to office-flex, to fully remote, depending on the requirements of their role. Red Hatters are encouraged to bring their best ideas, no matter their title or tenure. We're a leader in open source because of our open and inclusive environment. We hire creative, passionate people ready to contribute their ideas, help solve complex problems, and make an impact. Inclusion at Red Hat Red Hat’s culture is built on the open source principles of transparency, collaboration, and inclusion, where the best ideas can come from anywhere and anyone. When this is realized, it empowers people from different backgrounds, perspectives, and experiences to come together to share ideas, challenge the status quo, and drive innovation. Our aspiration is that everyone experiences this culture with equal opportunity and access, and that all voices are not only heard but also celebrated. We hope you will join our celebration, and we welcome and encourage applicants from all the beautiful dimensions that compose our global village. Equal Opportunity Policy (EEO) Red Hat is proud to be an equal opportunity workplace and an affirmative action employer. We review applications for employment without regard to their race, color, religion, sex, sexual orientation, gender identity, national origin, ancestry, citizenship, age, veteran status, genetic information, physical or mental disability, medical condition, marital status, or any other basis prohibited by law. Red Hat does not seek or accept unsolicited resumes or CVs from recruitment agencies. We are not responsible for, and will not pay, any fees, commissions, or any other payment related to unsolicited resumes or CVs except as required in a written contract between Red Hat and the recruitment agency or party requesting payment of a fee. Red Hat supports individuals with disabilities and provides reasonable accommodations to job applicants. If you need assistance completing our online job application, email application-assistance@redhat.com. General inquiries, such as those regarding the status of a job application, will not receive a reply. We’re the world’s leading provider of enterprise open source solutions—including Linux, cloud, container, and Kubernetes. We deliver hardened solutions that make it easier for enterprises to work across platforms and environments, from the core datacenter to the network edge. At Red Hat, our commitment to open source extends beyond technology into virtually everything we do. We collaborate and share ideas, create inclusive communities, and welcome diverse perspectives from all Red Hatters, no matter their role. It’s what makes us who we are. Some of the most knowledgeable and passionate people in the technology industry work here. Whether we’re building software, championing our products, or training new associates, we’re collaborating openly to make a difference in the world of open source and beyond.

Responsibilities

You will be responsible for characterizing, modeling, and enhancing the performance of distributed systems for Large Language Models. This includes defining KPIs, executing performance benchmarks, and collaborating with cross-functional teams to address performance issues.