Senior Machine Learning Engineer, LLM Inference Optimization

📋 Description

• Own optimization initiatives for specific model families, customer endpoints, and inference serving
• Evaluate inference engines and recommend practical serving configurations based on workload
• Diagnose and resolve model quality, performance, and reliability regressions during production
• Optimize LLM and VLM endpoints for latency, throughput, memory efficiency, GPU utilization, model
• Deploy, configure, benchmark, and extend modern inference engines such as vLLM, SGLang
• Build and productionize model-compression workflows, including quantization, quantization-aware

🎯 Requirements

• Strong software engineering skills in Python and PyTorch.
• Hands-on experience deploying, operating, or optimizing LLM, VLM, or high-throughput transformer
• Practical experience with at least one modern inference stack, such as vLLM, SGLang, TensorRT-LLM
• Strong understanding of transformer inference bottlenecks, including KV cache, attention
• Ability to reason quantitatively about latency, throughput, model quality, resource utilization
• Experience diagnosing complex performance problems and translating findings into production

🎁 Benefits

• Competitive compensation.
• Career growth and continuous learning opportunities.
• Flexibility and significant ownership over technical work.
• Collaborative and innovative working environment.
• Opportunity to work on impactful AI infrastructure and inference optimization projects.
• Exposure to advanced LLM and VLM serving technologies and large-scale AI workloads.