Runpod

Machine Learning Engineer

• Define inference performance measurements, including throughput, time to first token, inter-token latency, and cost per token
• Build tooling that makes performance measurements rigorous and repeatable
• Profile and diagnose performance problems across the serving stack, from scheduling and memory management to kernels and interconnect
• Improve serving efficiency for large, state-of-the-art models on single-node and multi-node GPU deployments
• Turn findings into production-ready runtimes, configurations, and defaults
• Collaborate with product and infrastructure teams to shape how inference is offered on Runpod
• Monitor the fast-moving inference ecosystem and evaluate what to adopt, build, or contribute back
• Trace serving engine/runtime bottlenecks and implement fixes when configuration tuning is insufficient
• Own LLM serving performance end to end across models, hardware generations, and workloads

Senior ML Systems Engineer, Inference

Account Manager

• Own a concentrated portfolio of fewer than 20 of Runpod's largest strategic accounts
• Manage account relationships, retention, and expansion
• Conduct monthly or more frequent executive and technical touchpoints
• Create deep account plans and multi-year growth strategies
• Partner with dedicated Forward Deployed Engineers to align technical outcomes with commercial expansion
• Introduce Runpod capabilities, roadmap updates, and ideas that drive new use cases and increased spend
• Drive complex renewals and expansions, negotiating multi-year commercial terms, pricing, and SLAs
• Build executive relationships and conduct strategic business reviews
• Represent strategic customer needs internally, influencing product, engineering, and supply priorities
• Maintain account plans, forecasts, and health/expansion metrics in the CRM
• Report account performance to leadership
• Travel periodically to visit strategic accounts and attend key industry events

Account Manager – Strategic

Infrastructure Engineer

• Validate new hardware and ensure partner deployments meet Runpod specifications for distributed AI/ML workloads
• Monitor fleet health and identify performance degradation
• Audit downtime and provide technical data needed to protect customer SLAs
• Use LLMs and AI agents to automate network triage and generate dynamic fleet runbooks
• Coordinate technical incident communications and translate outages into actionable resolutions
• Support the growth of infrastructure partners
• Own the technical lifecycle and operational health of Runpod’s high-density GPU fleet
• Serve as infrastructure advisor, technical translator, adopter, and incident commander for hardware partners
• Bridge hardware partners and internal engineering teams

Datacenter Infrastructure Specialist

Business Intelligence Analyst

• Lead, coach, and grow a team of analysts and BI practitioners
• Hire, develop, retain, prioritize, and raise the technical bar of analytics practitioners
• Drive company strategy by identifying data levers, quantifying opportunities, and delivering actionable recommendations
• Own the core metric layer, including utilization, retention, net revenue retention, margin, and marketplace supply/demand health
• Set the analytics roadmap with Product, Finance, and Go-to-Market leadership
• Analyze consumption-based revenue and customer behavior, including cohort retention, usage expansion and churn, savings plan adoption, spot versus reserved mix, and serverless workload economics
• Build a self-serve analytics layer for routine stakeholder questions
• Partner with Data Engineering on modeling, data quality, freshness, and SOC 2 requirements
• Establish experimentation and measurement practices and interpretation guardrails
• Represent analytics in executive and board-level reporting
• Translate ambiguous business questions into analysis and clear recommendations

Senior ML Systems Engineer, Inference

Account Manager – Strategic

Datacenter Infrastructure Specialist

Head of Analytics and Business Intelligence