Founding ML Systems Engineer – High-Performance AI Infra

Strativ Group; Palo Alto (CA); On-site; USD 450,000 - 550,000; Full time

Benefits offered by this job

Founding equity

Direct exposure to founders

Competitive compensation

Job summary

Strativ Group in Palo Alto is building production infrastructure for large-scale AI workloads, focusing on high-performance TPU and GPU inference, distributed model serving, and autonomous agent systems.

You will own critical components from day one, work directly with the founders, and influence the architectural direction and long-term strategy while optimizing latency, throughput, and cost. This is a genuinely early founding-team opportunity with meaningful equity.

Qualifications

• Background in ML systems or AI infrastructure required or highly desirable.
• Experience with model inference or serving.
• Background in distributed training or inference.
• Experience with GPU/TPU systems and low-latency distributed systems.
• Familiarity with scheduling, runtimes, or compiler-level optimization.

Responsibilities

• Build and optimize production infrastructure for large-scale AI workloads.
• Focus on high-performance TPU and GPU inference.
• Enable distributed model serving and scheduling.
• Optimize runtime, latency, throughput, and infrastructure cost.
• Ensure reliability, observability, and deployment for autonomous workloads.

Skills

ML systems

AI infrastructure

Model inference

Distributed training

GPU systems

TPU systems

Low-latency systems

Scheduling

Runtime optimization

Compiler optimization

Job description

Strativ Group in Palo Alto is building production infrastructure for large-scale AI workloads, focusing on high-performance TPU and GPU inference, distributed model serving, and autonomous agent systems.

You will own critical components from day one, work directly with the founders, and influence the architectural direction and long-term strategy while optimizing latency, throughput, and cost. This is a genuinely early founding-team opportunity with meaningful equity.