Senior Software Engineer - ML Infrastructure

Claryo; San Francisco (CA); On-site; USD 180,000 - 240,000; Full time

Benefits offered by this job

Competitive benefits package

Top-tier medical, dental, and vision

401k with employer matching

Parental leave

Unlimited vacation

Job summary

Claryo is seeking a Senior Software Engineer - ML Infrastructure to own end-to-end ML vision model lifecycles, from training pipelines to optimized cloud deployment. You will build scalable GPU compute clusters and robust orchestration to support real-time perception and autonomous decision-making in our AI-powered warehouse platform.

You’ll collaborate with research scientists and CV engineers to bridge experimentation and production-ready systems across SF-office infrastructure, ensuring

Qualifications

• 5+ years of professional software engineering experience.
• 3+ years in machine learning—deploying large-scale ML systems.
• B.S./M.S. in Computer Science, Robotics, or similar technical field.
• Experience deploying machine learning models in production (vision).
• Strong programming skills in Python.

Responsibilities

• Build end-to-end ML pipelines from data ingestion through model training, evaluation, and deployment.
• Train, evaluate, deploy and optimize state-of-the-art ML models in the cloud using platforms and inference optimization techniques.
• Establish monitoring, benchmarking, and evaluation frameworks to ensure model performance and reliability in production environments.
• Collaborate with research scientists, CV engineers, and product teams to bridge experiments and production-ready systems.

Skills

Python

C++

CUDA

GPU acceleration

Distributed systems

Education

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

Tools

PyTorch

TensorFlow

DeepSpeed

Ray

TorchServe

NVIDIA Triton Inference Server

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 Machine Learning Engineer to build and scale the infrastructure that powers our AI-driven warehouse intelligence platform. You'll own the end-to-end lifecycle of ML 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, computer vision and distributed systems. 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

Build end-to-end ML pipelines — from data ingestion and preprocessing through model training, evaluation, and deployment — and integrate them into core product workflows.

Train, evaluate, deploy and optimize state-of-the-art machine learning models in the cloud using platforms and inference optimization techniques, including VLMs and VLAs.

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.

5+ years of professional software engineering experience.

3+ years in machine learning— developing, scaling, deploying, and optimizing large-scale ML systems from data to model.

Track record of deploying machine learning models in production environments.

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

Strong programming skills in Python.

Preferred Experience

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

Proficiency with ML frameworks (PyTorch, TensorFlow, DeepSpeed, Ray) 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.

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

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.