Data Infrastructure Engineer

Pivot Robots, Inc.; San Francisco, Northern (CA, KY); Hybrid; USD 120,000 - 190,000; Full time

Job summary

Pivot Robots, Inc. in San Francisco is seeking a data infrastructure engineer to design schemas, build AWS-based data pipelines, and create an artifact store for scans, meshes, and calibration files.

You will build edge-to-cloud pipelines between robotic cells and infrastructure, develop ML training pipelines, dataset versioning, and model deployment while collaborating across the stack and traveling to customer sites as needed.

Qualifications

• 2+ years building data infrastructure on AWS (application-side, not platform operations).
• Strong schema design and data modeling, including distributed systems tradeoffs.
• ML infrastructure experience.
• Ability to work across the stack, from analyzing data to designing the systems around it.
• Willingness to travel to customer sites.

Responsibilities

• Design and own the schemas and data models behind our production systems.
• Build and maintain data infrastructure on AWS.
• Build the artifact store for scans, meshes, model checkpoints, and calibration files.
• Build edge-to-cloud pipelines between robotic cells and our infrastructure.
• Build ML infrastructure: training pipelines, dataset versioning, and model deployment.

Skills

AWS data infrastructure

Schema design & data modeling

ML infrastructure

Full-stack data systems

Willingness to travel

Tools

AWS

Edge computing

Job description

Responsibilities

• Design and own the schemas and data models behind our production systems

• Build and maintain data infrastructure on AWS

• Build the artifact store for scans, meshes, model checkpoints, and calibration files

• Build edge-to-cloud pipelines between robotic cells and our infrastructure

• Build ML infrastructure: training pipelines, dataset versioning, and model deployment

Requirements

• 2+ years building data infrastructure on AWS (application-side, not platform operations)

• Strong schema design and data modeling, including distributed systems tradeoffs

• ML infrastructure experience

• Ability to work across the stack, from analyzing data to designing the systems around it

• Willingness to travel to customer sites

Preferred

• Data infrastructure in a robotics, autonomy, or industrial IoT setting

• Edge computing experience

• Interest in manufacturing