Senior Software Engineer

Job Summary:

The Red Hat Performance and Scale Engineering organization is seeking a Senior Software Engineer to join the Performance and Scale for AI Platforms (PSAP) team. The PSAP team drives our MLPerf™ submissions that prove Red Hat’s AI platform can compete with - and often beat - other competitive stacks across training and inference workloads. You will own the end-to-end process of designing compliant test harnesses, running performance and power runs, collecting valid accuracy logs, and packaging results for public MLCommons leaderboards. Your work will shape Red Hat’s public reputation for AI performance leadership while directly influencing upstream MLPerf community engagements.

This position calls for a creative, adaptable engineer who is eager to learn new technologies and thrive in a dynamic, open source-oriented culture. You will be part of a centralized Red Hat performance engineering team that fosters innovation and collaboration to achieve world-class AI performance.

The broader mission of Red Hat’s Performance and Scale Engineering group is to establish performance and scale leadership across the Red Hat product and cloud services portfolio. Our scope ranges from component-level analysis to system-wide optimizations, working alongside engineering teams, product management, product marketing, and customer support, as well as Red Hat’s extensive ecosystem of hardware and software partners.

What you will do:

• Design performance test plans for new MLPerf Training and Inference suites (datacenter & edge) covering LLMs primarily.

• Execute accuracy, performance and power submissions; triage regressions and drive improvements using LoadGen logs, traces, and other profiling tools.

• Build and maintain highly optimized container-based harnesses (Podman/Kubernetes) for benchmark execution, dataset pre-processing steps and compliance checks for reproducible CI execution.

• Profile kernels, GPU runtimes and distributed collectives; propose patches to Red Hat AI software stack to remove bottlenecks revealed by MLPerf™ results.

• Represent Red Hat in MLCommons™ working groups; upstream fixes and new benchmark proposals.

• Present results and best practices at premier open source and industry conferences; author technical blogs and white papers that translate benchmark data into customer value.

What you will bring:

• 3+ years of relevant industry experience in performance engineering or ML infrastructure

• Hands-on MLPerf (Training or Inference) harness work 

• Strong Python & Bash proficiency plus one systems language (Go/Rust/C++)

• Expert Linux skills (cgroups, scheduler, perf, NUMA, GPU drivers, etc)

• Experience with container orchestration (Kubernetes, OpenShift)

• Performance-profiling literacy (nvprof, Nsight Systems, perf, eBPF)

• Clear written & spoken English

The following will be considered a plus:

• Master’s or PhD in Computer Science, AI, or a related field

• Prior MLPerf submission ownership or MLCommons working-group membership

• Deep knowledge of LLM inference runtimes

• Contributions to PyTorch or TensorFlow performance patches

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The salary range for this position is $127,890.00 - $211,180.00. Actual offer will be based on your qualifications.

Pay Transparency

Red Hat determines compensation based on several factors including but not limited to job location, experience, applicable skills and training, external market value, and internal pay equity. Annual salary is one component of Red Hat’s compensation package. This position may also be eligible for bonus, commission, and/or equity. For positions with Remote-US locations, the actual salary range for the position may differ based on location but will be commensurate with job duties and relevant work experience. 

About Red Hat

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