about 5 hours ago
Base Salary
$200k - $300k/yr
Responsibilities
- Own the technical direction and roadmap for Reducto's ML infrastructure.
- Build and maintain the training and inference stack for high-performance production serving.
- Optimize model serving at every layer, including kernels and distributed inference.
- Design systems for reliable multi-node, multi-GPU training and inference.
- Improve GPU utilization, latency, throughput, and cost efficiency.
- Develop benchmarks to identify bottlenecks and guide infrastructure investments.
- Evaluate and apply state-of-the-art advances in training and inference.
- Build tooling to help ML engineers transition from experiments to production.
- Collaborate with ML and Platform engineers on architecture and capacity planning.
- Raise the engineering bar through design reviews and mentorship.
Requirements
- 5+ years of experience building production infrastructure with significant ML systems experience.
- Experience leading complex technical projects from problem identification to production deployment.
- Strong Python and systems-engineering skills.
- Understanding of performance characteristics of modern GPU workloads.
- Familiarity with Kubernetes and distributed training or serving frameworks.
- Ability to reason across low-level model performance and higher-level platform architecture.
- High standards for quality, precision, and operational reliability.
- Ability to thrive in a fast-changing, high-growth environment.
Benefits
- Unlimited PTO for recharging.
- Free daily lunch with teammates in the office.
- Commuter reimbursement for transportation costs.
- Comprehensive medical, dental, and vision insurance.
- Health and wellness budget of up to $150 per month.
- Flexible parental leave scheduling.