MTS 2, AI Platform Engineer

5+ years of strong development experience

Experience deploying and operating LLM inference services in production.

Strong production coding skills in Python plus Go or Rust (systems-level implementation and debugging).

Experience with ML frameworks and runtimes: PyTorch, vLLM, SGLang (and/or TensorRT).

Knowledge of GPU architecture and performance (profiling, memory bandwidth/latency tradeoffs); CUDA/kernel programming is a strong plus.

Solid understanding of LLM inference and optimization techniques: continuous batching, KV cache management, quantization, speculative decoding (nice-to-have), etc.

3+ years hands-on experience in performance optimization and systems programming for AI/ML workloads.

Demonstrated ability to deliver measurable production improvements (e.g., 2X throughput, lower p95/p99 latency, reduced GPU cost).

Proven skill in root-cause analysis: finding bottlenecks across model, runtime, networking, and infrastructure.

Demonstrated proficiency in applying autonomous AI coding agents to speed up software delivery pipelines. This includes advanced prompting and careful human-in-the-loop code review to improve development speed and code accuracy.

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