Senior Machine Learning Engineer

Posted Yesterday
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Boston, MA, USA
In-Office
186K-287K Annually
Senior level
Cloud • Information Technology • Internet of Things • Software • Consulting • Infrastructure as a Service (IaaS) • Automation
Creating better technology the open source way
The Role
Lead the design, optimization, and production deployment of high-performance LLM inference systems using vLLM, CUDA, Triton, C++, and Python. Improve GPU utilization, latency, throughput, scalability, and cost through kernel optimization, quantization, batching, memory management, distributed inference, and profiling. Contribute to upstream open-source projects, establish engineering standards, review performance-critical code, and guide research-driven serving improvements.
Summary Generated by Built In

*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)
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 [email protected]. General inquiries, such as those regarding the status of a job application, will not receive a reply. 

Skills Required

  • Master's degree in Computer Science, Computer Engineering, or a related field, plus three years of experience in the job offered or a related role
  • Bachelor's degree in Computer Science, Computer Engineering, or a related field, plus five years of experience in the job offered or a related role
  • Three years of experience with high-performance Python and modern C++ development
  • Three years of experience with performance analysis, benchmarking, and profiling on NVIDIA GPUs using Nsight or similar tools
  • Three years of experience with GPU memory architecture and memory optimization for deep learning workloads
  • Two years of experience making open-source pull requests to PyTorch or vLLM
  • Two years of experience with CUDA, Triton, or CUTLASS kernel optimization
  • Two years of experience with LLM inference optimization, including quantization, KV cache, or batching
  • Two years of experience with distributed computing, including inter- and intra-GPU communication protocols
  • Two years of experience leading technical design and reviewing performance-critical code

Red Hat Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Red Hat and has not been reviewed or approved by Red Hat.

  • Healthcare Strength — Healthcare coverage is presented as comprehensive, spanning medical, dental, and vision along with life and disability coverage. Access to HSA/FSA options and broadly positive reception of health benefits support the view that healthcare is a core strength.
  • Leave & Time Off Breadth — Time-off offerings are described as generous, with substantial PTO for new hires plus additional recharge days and an end-of-year shutdown for many non-critical roles. Paid volunteer time, holidays, sick days, and supportive expectations around taking time off reinforce the breadth of leave benefits.
  • Strong & Reliable Incentives — The rewards package includes performance bonuses and a recurring quarterly bonus program tied to company and individual performance. Availability of ESPP participation further adds to incentive pathways beyond base pay.

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The Company
HQ: Raleigh, NC
20,000 Employees
Year Founded: 1993

What We Do

At Red Hat, we connect an innovative community of customers, partners, and contributors to deliver an open source stack of trusted, high-performing solutions. We offer cloud, Linux, middleware, storage, and virtualization technologies, together with award-winning global customer support, consulting, and implementation services. Red Hat is a rapidly growing company supporting more than 90% of Fortune 500 companies.

Why Work With Us

Red Hatters freely exchange different viewpoints, contribute ideas, and solve problems together. Our love of collaboration, accountability, a sense of community, and a measure of autonomy combine to create a powerful force that fosters innovation and makes Red Hat a great place to work.

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