ML Infra Tech Lead: High-Performance GPU & K8s

Reducto; Santa Fe (NM); On-site; USD 190,000 - 230,000; Full time

Benefits offered by this job

Unlimited PTO

Daily Lunch

Commuter Reimbursement

Comprehensive Insurance

Health and Wellness Budget

Parental Leave

Job summary

Reducto seeks an ML Infrastructure Tech Lead to own and optimize our high-performance infrastructure for model training and inference. You will drive architecture choices, implement scalable multi-GPU systems, and partner with ML and Platform teams to deliver production-ready software.

This hands-on leadership role requires deep Python and systems engineering skills, extensive experience with GPUs, and the ability to balance rapid experimentation with reliable production serving.

Qualifications

• Have 5+ years of experience building production infrastructure, including significant ML systems experience.
• Have led complex technical projects from an ambiguous problem through production deployment.
• Are equally comfortable setting direction and personally implementing the hardest parts.
• Have strong Python and systems-engineering skills.
• Understand the performance characteristics of modern GPU training or inference workloads.
• Are comfortable with Kubernetes and distributed training or serving frameworks.
• Can reason across low-level model performance and higher-level platform architecture.
• Hold yourself to a high bar for quality, precision, and operational reliability.
• Operate well in a fast-changing, high-growth environment.
• Take full ownership from strategy through execution.

Responsibilities

• Own the technical direction and roadmap for Reducto's ML infrastructure.
• Build and maintain our training and inference stack, balancing fast experimentation with high-performance production serving.
• Optimize model serving at every layer, including kernels, runtimes, batching, scheduling, and distributed inference.
• Design systems for reliable multi-node, multi-GPU training and inference.
• Improve GPU utilization, latency, throughput, reliability, observability, and cost efficiency.
• Develop benchmarks that identify bottlenecks and guide infrastructure investments.
• Evaluate state-of-the-art advances in training and inference and apply the ones that matter.
• Build the tooling and abstractions that help ML engineers move quickly from experiments to production.
• Partner with ML and Platform engineers on architecture, capacity planning, and technical prioritization.
• Raise the engineering bar through design reviews, mentorship, and hands-on technical leadership.

Skills

Python

Systems engineering

Kubernetes

Distributed training

GPU workloads

ML infrastructure

Tools

CUDA

Triton

PyTorch

Job description

Reducto seeks an ML Infrastructure Tech Lead to own and optimize our high-performance infrastructure for model training and inference. You will drive architecture choices, implement scalable multi-GPU systems, and partner with ML and Platform teams to deliver production-ready software.

This hands-on leadership role requires deep Python and systems engineering skills, extensive experience with GPUs, and the ability to balance rapid experimentation with reliable production serving.