Senior Machine Learning Engineer

Red Hat, LLC; Boston (MA); On-site; USD 186,000 - 287,000; Full time

Job summary

Red Hat, LLC in Boston seeks a senior engineer to lead the design and implementation of high-performance Python, C++, CUDA, and Triton code for vLLM-based inference systems in production-scale environments. You will drive performance profiling and optimization on NVIDIA GPUs, expanding kernel and memory optimizations while advancing end-to-end inference pipelines across multi-GPU deployments.

This role requires a strong track record in open-source contributions and advanced GPU computing

Qualifications

• Mastery of high‑performance Python and modern C++ for large‑scale inference.
• Experience profiling and optimizing GPU workloads with Nsight or equivalent.
• Familiarity with GPU memory architectures and deep learning optimizations.

Responsibilities

• Architect, develop, and optimize LLM inference algorithms for vLLM-based systems.
• Profile, benchmark, and model latency, throughput, and cost on NVIDIA GPUs.
• Own end-to-end optimization of inference pipelines across multi‑GPU deployments.
• Prototype and integrate cutting‑edge serving techniques from research.
• Set engineering standards, perform peer reviews, and guide testing.

Skills

Python

C++

GPU optimization

Performance profiling

Open-source contributions

Education

Master's degree in Computer Science or related field

Bachelor's degree in Computer Science or related field

Tools

CUDA

Triton

CUTLASS

Nsight Systems

Nsight Compute

CUPTI

Job description

*Telecommuting permitted: work may be performed within normal commuting distance from the Red Hat, LLC office in Boston, MA.

Lead the design and implementation of high-performance Python, C++, CUDA, and Triton code for vLLM-based inference systems, GPU kernels, and numerical computing components in production-scale LLM serving environments.

What You Will Do

Architect, develop, and optimize advanced LLM inference algorithms, including quantization, sparsification, speculative decoding, paged attention, KV cache optimization, batching, scheduling, and memory management, to significantly improve latency, throughput, scalability, and cost efficiency.

Drive deep performance profiling, benchmarking, and modeling on NVIDIA GPUs, using tools such as Nsight Systems, Nsight Compute, CUPTI, PyTorch Profiler, CUDA, Triton, and CUTLASS to identify bottlenecks and deliver measurable system-level improvements.

Own the end-to-end optimization of vLLM-based inference pipelines, including kernel-level tuning, runtime optimization, distributed inference, multi-GPU serving, tensor/pipeline parallelism, and large-scale deployment performance.

Evaluate, prototype, and integrate state-of-the-art LLM serving techniques from cutting-edge research and open-source communities, including quantization, sparsity, speculative decoding, continuous batching, prefix caching, attention optimization, and model compression.

Set engineering standards for performance-critical code, conduct rigorous peer reviews, guide testing and benchmarking strategies, and leverage AI-assisted development tools to maintain high code quality, reliability, and maintainability.

Contribute to and maintain upstream open-source ML infrastructure vLLM, including reviewing pull requests, triaging issues, participating in design discussions, and supporting release readiness.

Stay at the forefront of LLM systems research and GPU computing advancements, proactively identifying opportunities to improve the product through emerging techniques in serving efficiency, hardware utilization, and model acceleration.

What You Will Bring

Master's degree (U.S. or foreign equivalent) in Computer Science, Computer Engineering, or related field and three (3) years of experience in the job offered or related role OR Bachelor's degree (U.S. or foreign equivalent) in Computer Science, Computer Engineering, or related field and five (5) years of experience in the job offered or related role.

• Must have three (3) years of experience with: high-performance Python and Modern C++ development; performance analysis, benchmarking, and profiling on NVIDIA GPUs using Nsight or similar tools; and GPU memory architecture and memory optimization for deep learning workloads.
• Must have two (2) years of experience with: making open-source pull requests to PyTorch or vLLM; CUDA, Triton, or CUTLASS kernel optimization; LLM inference optimization, including quantization, KV cache or batching; distributed computing including inter and intra GPU communication protocols; and leading technical design, reviewing performance-critical code.

#LI-DNI

The salary range for this position is $186,160 - $287,410/year. 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

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)

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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.