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Peano AI

Founding Machine Learning Infrastructure Engineer

Applied Machine LearningConfirmed live in the last 24 hours
Full-timePalo Alto, CA, USA

About the Job

Requirements

  • Strong experience in machine learning systems, distributed systems, or high-performance computing.
  • Experience optimizing inference or training workloads for large models.
  • Familiarity with TPUs, GPUs, or other accelerators.
  • Experience with one or more of CUDA, Triton, NCCL, JAX/XLA, PyTorch internals, vLLM, SGLang, TensorRT-LLM, distributed inference, or distributed training.
  • Strong systems debugging skills.
  • Comfort working across model code, runtime, infrastructure, and product requirements.
  • Ability to operate effectively in an early-stage startup environment.
  • Ability to take end-to-end ownership, from design to implementation to production outcomes.
  • Ability to do deep, focused work and sustain execution.
  • Comfort with ambiguity, rapid change, and wearing multiple hats.

Responsibilities

  • Optimize large-scale large language model inference and serving systems.
  • Improve total tokens per second, decode tokens per second, latency, throughput, and cost efficiency.
  • Work on serving infrastructure for open-source models across different types of accelerators.
  • Improve batching, scheduling, key-value cache management, memory usage, and accelerator utilization.
  • Support long-context inference, including workloads targeting up to 1 million tokens of context.
  • Debug performance bottlenecks across model execution, runtime, networking, and infrastructure.
  • Work with frameworks such as JAX/XLA, PyTorch, vLLM, SGLang, TensorRT-LLM, or related systems.
  • Collaborate closely with the application team to ensure infrastructure is optimized for agentic workloads, not just generic chatbot inference.
  • Help turn research prototypes into reliable, high-performance production systems.
  • Ship quickly, learn from failures, and iterate.
  • Focus on real customer impact during critical milestones.

Desired Qualifications

  • Direct TPU experience is a strong plus, but not required.
  • Hands-on technical excellence and strong engineering judgment.
  • Communicate clearly with teammates, customers, and stakeholders.
  • Maintain low ego, high integrity, high accountability, and strong collaboration.
  • Continuously learn and apply judgment, intelligence, and capability to improve over time.

About the Company

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