Senior AI/ML Infrastructure Engineer

Theory Ventures; San Francisco (CA); Hybrid; USD 180,000 - 280,000; Full time

Job summary

BackOps is building the AI resolution layer for enterprises managing physical goods. You will design and own the AI/ML infrastructure powering Relay, enabling reliable, scalable model execution across complex enterprise workflows.

As a senior engineer, you will balance performance, cost, and quality, making foundational technical decisions and working closely with the CTO and engineering teams to advance our intelligence and production readiness.

Qualifications

• Have 6+ years of relevant software engineering experience with ownership of complex systems.
• Built, deployed, or optimized production AI/ML infrastructure or model-serving systems.
• Strong Python proficiency and experience with distributed systems.

Responsibilities

• Own the architecture and engineering of AI/ML systems powering Relay.
• Build model-serving, inference pipelines, and execution infrastructure.
• Optimize latency, throughput, scalability, and inference cost.
• Drive model evaluation, benchmarking, and production quality improvements.
• Engineer reliability into production AI with observability and failure recovery.
• Collaborate with product and engineering to connect improvements to outcomes.

Skills

Python

Distributed systems

Production AI

Model serving

Performance debugging

System architecture

Tools

PyTorch

Hugging Face

vLLM

Triton

Kubernetes

Ray

Job description

BackOps is building the AI resolution layer for enterprises managing physical goods. You will design and own the AI/ML infrastructure powering Relay, enabling reliable, scalable model execution across complex enterprise workflows.

As a senior engineer, you will balance performance, cost, and quality, making foundational technical decisions and working closely with the CTO and engineering teams to advance our intelligence and production readiness.