Senior ML Infra Engineer — Real-Time Vision & Cloud GPUs

Claryo; San Francisco, Northern (CA, KY); Hybrid; USD 180,000 - 240,000; Full time

Benefits offered by this job

Medical/Dental/Vision

401k with employer matching

Parental leave

Unlimited vacation

Job summary

Claryo seeks a Senior Software Engineer - ML Infrastructure to build and scale infrastructure powering our AI-driven warehouse intelligence platform. You will own the end-to-end lifecycle of computer vision models—from training pipelines through optimized cloud deployment—ensuring high reliability and low-latency production systems.

This deeply technical role sits at the intersection of machine learning, distributed systems, and cloud infrastructure.

Qualifications

• BS/MS in CS, robotics, or related field.
• 7+ years software engineering with ML infra experience.

Responsibilities

• Develop and maintain distributed cloud GPU infrastructure for large-scale world model training and low-latency inference.
• Build end-to-end computer vision pipelines—from data ingestion to deployment—into core product workflows.
• Deploy and optimize ML models in the cloud using model serving platforms and inference optimization techniques.
• Design and operate orchestration systems for ML pipelines for engineers and non-engineers.
• Establish monitoring, benchmarking and evaluation frameworks for production models.

Skills

Python

C++/CUDA

Distributed systems

PyTorch/TensorFlow

GPU infrastructure

Cloud platforms

Model serving

Education

B.S./M.S. in Computer Science or related field

Tools

Kafka

gRPC

ROS2

Flyte

Temporal

Airflow

TorchServe

TensorRT

Job description

Claryo seeks a Senior Software Engineer - ML Infrastructure to build and scale infrastructure powering our AI-driven warehouse intelligence platform. You will own the end-to-end lifecycle of computer vision models—from training pipelines through optimized cloud deployment—ensuring high reliability and low-latency production systems.

This deeply technical role sits at the intersection of machine learning, distributed systems, and cloud infrastructure.