Senior Software Engineer - ML Infrastructure

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

Senior Software Engineer - ML Infrastructure

Location

Employment Type

Full time

Location Type

On-site

Department

Compensation

We’re looking for a Senior Software Engineer - ML Infrastructure to build and scale the infrastructure that powers our AI-driven warehouse intelligence platform. You’ll own the end-to-end lifecycle of computer vision models — from training pipelines through optimized cloud deployment — ensuring our cutting-edge computer vision and multi-modal AI systems run reliably and efficiently in production. Your work will directly enable the real-time perception and autonomous decision-making capabilities at the core of our platform.

This is a deeply technical role at the intersection of machine learning, distributed systems, and cloud infrastructure. You’ll design scalable GPU compute clusters, build robust orchestration pipelines, and optimize model serving for low-latency inference at scale. You’ll work closely with our research scientists, computer vision engineers, and product teams to bridge the gap between experimental models and production-ready systems that operate across diverse warehouse environments. We’ve found tremendous value in collaborative problem-solving, thus our team works from our SF office three days a week.

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 and preprocessing through model training, evaluation, and deployment — and integrate them into core product workflows.

Deploy and optimize state-of-the-art machine learning models in the cloud using model serving platforms and inference optimization techniques, including VLMs and VLAs.

Design and operate orchestration systems that enable both engineers and non-engineers to build and manage data and ML pipelines.

Establish monitoring, benchmarking, and evaluation frameworks to ensure model performance and reliability in production environments.

Required Experience

B.S. / M.S. in Computer Science, Robotics, or similar technical field, or equivalent practical experience.

7+ years of professional software engineering experience, with at least 3 years in machine learning infrastructure — developing, scaling, training, deploying, and optimizing large-scale ML systems from data to model.

Track record of deploying machine learning models in production environments with real-world constraints.

Experience with distributed messaging and compute systems (Kafka, gRPC, ROS2, or similar).

Strong programming skills in Python with solid software engineering practices.

Preferred Experience

Experience with training and/or deployment of machine learning models in the computer vision domain.

Experience developing, running, and managing orchestration systems (Flyte, Temporal, Airflow, or similar) for ML and data pipelines.

Proficiency with ML frameworks (PyTorch, TensorFlow, DeepSpeed) and model serving platforms (TorchServe, TensorFlow Serving, NVIDIA Triton Inference Server, or similar).

Deep understanding of state-of-the‑art machine learning models such as auto‑regressive transformers and familiarity with inference optimization techniques (TensorRT, quantization, custom kernels).

Experience with C++ or CUDA programming for GPU acceleration.

Prior experience working at autonomous vehicles or robotics companies.

Equal Opportunity Statement

We’re an equal opportunity employer that values diversity and inclusion. We welcome teammates of all backgrounds and don’t discriminate based on race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or veteran status.

At Claryo, we offer a competitive benefits package that supports your health and well-being, including — top-tier medical, dental, and vision coverage, 401k with employer matching, parental leave, and unlimited vacation.