This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior Machine Learning Engineer, LLM Inference Optimization based in Netherlands.

• Own optimization initiatives for specific model families, customer endpoints, and inference serving backends.
• Evaluate inference engines and recommend practical serving configurations based on workload requirements.
• Diagnose and resolve model quality, performance, and reliability regressions during production rollouts.
• Optimize LLM and VLM endpoints for latency, throughput, memory efficiency, GPU utilization, model quality, and cost per token.
• Deploy, configure, benchmark, and extend modern inference engines such as vLLM, SGLang, TensorRT-LLM, Triton Inference Server, NVIDIA Dynamo, or equivalent technologies.
• Build and productionize model-compression workflows, including quantization, quantization-aware training, distillation, low-bit serving, and accuracy recovery.
• Implement or integrate advanced inference techniques such as speculative decoding, draft models, KV-cache optimization, prefix caching, chunked prefill, continuous batching, and disaggregated prefill/decode serving.
• Develop reproducible benchmark harnesses covering TTFT, TPOT, tokens per second per GPU, p95/p99 latency, GPU memory usage, reliability, and cost per token.
• Partner with GPU kernel and platform engineers to identify bottlenecks across model code, kernels, runtimes, schedulers, gateways, and cluster infrastructure.