Data Infrastructure Engineer for AI & Robotics Platforms

Insight Recruitment; Redwood City (CA); On-site; USD 150,000 - 230,000; Full time

Job summary

Insight Recruitment is seeking a Software Engineer, Data Infrastructure for a well-funded robotics and AI company in Redwood City, onsite. You will design and build data platforms to support large-scale ML and robotics research, handling multimodal data pipelines and production-ready models.

Collaborate with ML researchers and robotics engineers; responsibilities include data storage, processing, labeling, evaluation, and tooling.

Qualifications

• Bachelor's or Master's degree in Computer Science, Software Engineering, Data Engineering, or related discipline.
• 5+ years of professional software engineering experience.
• Experience with NumPy, backend services, and distributed systems.
• Strong understanding of cloud infrastructure and data-intensive applications.
• Experience with Redis and MongoDB; AWS and/or GCP experience.

Responsibilities

• Design and develop scalable data infrastructure and platforms for multimodal robotics and AI datasets.
• Build pipelines for video, sensor data, trajectories, time-series, and 3D data.
• Develop dashboards, analytics tools, and debugging platforms for researchers.
• Collaborate with ML engineers, researchers, and product teams to shape the data platform roadmap.

Skills

Backend development

Distributed systems

Cloud infrastructure

Data-intensive applications

Problem solving

Education

Bachelor's or Master’s in CS/SE/Data Eng

5+ years software engineering

Tools

NumPy

Redis

MongoDB

AWS

GCP

Docker

Airflow

Weights & Biases

MLflow

React

TypeScript

Job description

Insight Recruitment is seeking a Software Engineer, Data Infrastructure for a well-funded robotics and AI company in Redwood City, onsite. You will design and build data platforms to support large-scale ML and robotics research, handling multimodal data pipelines and production-ready models.

Collaborate with ML researchers and robotics engineers; responsibilities include data storage, processing, labeling, evaluation, and tooling.