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.

Requirements

5+ years of overall software engineering experience, including at least 3 years focused on performance engineering or systems-level development.
Strong understanding of operating systems and distributed systems
Foundational knowledge of AI and LLM inference workflows
Proficiency in Python for data and machine learning workflows, along with strong Linux and Bash skills
Excellent communication skills, with the ability to translate performance data into clear business and customer value
Passion for and commitment to open source principles
Master’s or PhD in Computer Science, AI, or a related field is considered a plus
Experience contributing to open source projects or leading community initiatives
Hands on experience with Kubernetes or OpenShift
Familiarity with performance and observability tools such as perf, eBPF tools, Nsight Systems, and PyTorch Profiler
Experience with modern LLM inference stacks such as vLLM, TensorRT LLM, Hugging Face TGI, and Triton Inference Server

Benefits

Comprehensive medical, dental, and vision coverage
Flexible Spending Account - healthcare and dependent care
Health Savings Account - high deductible medical plan
Retirement 401(k) with employer match
Paid time off and holidays
Paid parental leave plans for all new parents
Leave benefits including disability, paid family medical leave, and paid military leave
Additional benefits including employee stock purchase plan, family planning reimbursement, tuition reimbursement, transportation expense account, employee assistance program, and more!

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

performance engineeringsystems-level developmentPythonLinuxBashKubernetesOpenShiftAILLM inference workflowsperformance benchmarking

Soft Skills

communicationcollaborationdata analysisproblem-solvingpresentationreportingcommunity leadershipcustomer focusopen source commitmentproactive exploration

Certifications

Master’s in Computer SciencePhD in Computer ScienceAI certification