Machine Learning Engineer — Inference Optimization

Responsibilities:

• Optimize ML inference systems to improve latency, throughput, scalability, and cost.
• Profile and identify bottlenecks across GPU and CPU inference pipelines.
• Implement advanced optimization techniques such as quantization, KV-cache optimization, and speculative decoding.

Requirements:

• Strong experience in ML inference optimization and high-performance systems.
• Deep understanding of neural network architectures, attention mechanisms, and compute graphs.
• Hands-on experience with PyTorch, CUDA, and inference frameworks like TensorRT or vLLM.

Benefits:

• Competitive compensation package with meaningful equity participation.
• Opportunity to work on performance-critical AI systems with direct product impact.
• Flexible remote work environment and a culture that values technical excellence.