Applied AI Engineer, Inference

📋 Description

• Build benchmarking workflows to measure latency, throughput, quality regressions, and cost.
• Benchmark inference stack against realistic workloads and baselines to identify gaps.
• Profile model-serving across frameworks, runtimes, and hardware to find bottlenecks.
• Drive optimizations for customer workloads, tuning serving configs and validating changes.
• Design and run experiments on model-serving techniques like quantization and caching.
• Partner with inference engineers to productionize improvements and tests.

🎯 Requirements

• 4+ years of experience in machine learning, systems, performance engineering, or adjacent applied engineering work.
• Strong Python programming and comfort working in production engineering environments.
• Experience running empirical evaluations, benchmarks, or experiments and translating results into concrete engineering decisions.
• Familiarity with LLM inference systems and tools such as vLLM, SGLang, TensorRT-LLM, or similar model-serving stacks.
• Understanding of practical tradeoffs involved in latency, throughput, batching, GPU utilization, quantization, and quality regression analysis.
• Ability to work across model, systems, and product boundaries and stay focused on outcomes that matter for customers.

🎁 Benefits

• Medical, dental, and vision insurance - 100% paid for by CoreWeave
• Company-paid Life Insurance
• Voluntary supplemental life insurance
• Short and long-term disability insurance
• Flexible Spending Account
• Health Savings Account