Enterprise AV Field Solutions Engineer

MaC VC; San Francisco (CA); On-site; USD 160,000 - 210,000; Full time

Job summary

Avala is seeking a technically adept engineer to embed our platform into customer perception pipelines and collaborate with enterprise AV and robotics teams. You will integrate data workflows, build connectors, and troubleshoot production data quality across multiple sensor modalities.

You will translate customer requirements into actionable platform enhancements and represent Avala in engineering meetings with ML researchers and managers, traveling 20–30% as needed.

Qualifications

• 4+ years in software engineering with customer-facing technical roles.
• Strong Python and systems programming experience.
• Understanding of autonomous vehicle or robotics perception stacks.
• Experience with sensor data — LiDAR, camera, radar, IMU.
• Excellent communication skills — you can work with ML researchers and engineering managers alike.
• Willingness to travel to customer sites (20-30%)

Responsibilities

• Embed Avala's platform into customer perception pipelines.
• Work with enterprise AV and robotics teams on integration.
• Build custom data connectors, export formats, and workflow automations.
• Troubleshoot production data quality issues across sensor modalities.
• Translate customer requirements into platform feature requests and product feedback.
• Represent Avala as a technical expert in customer engineering meetings

Skills

Software engineering

Python

Customer-facing communication

Systems programming

Sensor data expertise

Tools

ROS

MCAP

Sensor data formats

Job description

Avala is seeking a technically adept engineer to embed our platform into customer perception pipelines and collaborate with enterprise AV and robotics teams. You will integrate data workflows, build connectors, and troubleshoot production data quality across multiple sensor modalities.

You will translate customer requirements into actionable platform enhancements and represent Avala in engineering meetings with ML researchers and managers, traveling 20–30% as needed.