Senior ML Data Infrastructure Engineer

Nuro; California (MO); On-site; USD 194,000 - 352,000; Full time

Job summary

Nuro is building a universal autonomy platform and seeks a data-focused engineer to design scalable data pipelines, storage, and tooling for evaluation of autonomous driving systems. You will collaborate with ML and systems teams to validate deployments and improve data infrastructure.

The role emphasizes large-scale data processing, monitoring, and data annotation tooling, with a strong focus on reliability and performance. Competitive compensation and equity are offered.

Qualifications

• BS, MS, or Ph.D in CS/EE or related field with 4+ years of experience.
• Strong proficiency in Python or similar languages.
• Experience with large-scale data and building scalable data pipelines.
• Engineering leadership experience, setting vision and mentoring.
• Technical excellence and ability to drive standards across the organization.

Responsibilities

• Design and develop large-scale batch and streaming data pipelines for evaluation across use cases.
• Create a storage system for large volume and diverse evaluation metrics.
• Build dashboards and reports to compare ML components and system performance.
• Develop and maintain testing and monitoring to ensure data integrity and resilience of pipelines.
• Develop data mining tools to support Autonomy data discovery (Perception, Behavior, Mapping).
• Develop data annotation tools for internal and external labeling workflows to ensure high fidelity labels.
• Scale annotation labels with state-of-the-art ML techniques.

Skills

Python

Education

Bachelor's degree in Computer Science, Electrical Engineering, or closely related field

MS/PhD in a related field (advantage)

Tools

GCP

BigQuery

PostgreSQL

Job description

Nuro is building a universal autonomy platform and seeks a data-focused engineer to design scalable data pipelines, storage, and tooling for evaluation of autonomous driving systems. You will collaborate with ML and systems teams to validate deployments and improve data infrastructure.

The role emphasizes large-scale data processing, monitoring, and data annotation tooling, with a strong focus on reliability and performance. Competitive compensation and equity are offered.