Senior/Staff Software Engineer, ML Data Infrastructure

Nuro • Mountain View, CA

15d

About The Position

Nuro takes a machine-learning-first approach to autonomous driving technology. In an ML-first system, the overall system performance depends heavily on the quantity and diversity of its training and evaluation data. The team plays a crucial role in the advancement of autonomous driving systems by creating a scalable and reliable data infrastructure. This infrastructure is designed to produce training and evaluation data derived from both on-road collected logs and simulation logs. Additionally, the team collaborates closely with system engineers to thoroughly validate the autonomous driving system before its deployment.

Requirements

• You have a degree in BS, MS.c or Ph.D, plus 4 years of relevant work experience
• Strong proficiency in Python or similar languages
• Domain experience: Experience working with large-scale data and building scalable & reliable systems/data pipelines; ability to understand and design complex systems
• Engineering leadership: Experience setting team or project product and technical vision, timelines, and prioritization; being a Technical Lead, mentoring and support junior engineers
• Technical excellence: Ability and willingness to deep dive into implementation, driving technical standards and best practices across broader software organization
• A bachelor's degree in Computer Science, Electrical Engineering, or a closely related field

Nice To Haves

• Strong proficiency in C++ or other high-performance low-level languages
• Strong knowledge of GCP, GCS, BigQuery, or PostgreSQL
• Knowledge of data engineering, and its tooling and best practices
• Knowledge of batch and streaming data processing, warehousing, and analytics solutions
• Experience working with large-scale distributed data systems
• Experience with system & framework design
• Experience with data workflow orchestration platforms

Responsibilities

• Design and develop unified, introspectable, large-scale batch and streaming data pipelines that can ingest and process data across a wide range of use cases relevant to evaluation.
• Create and implement a storage system capable of accommodating both the large volume and diverse range of evaluation and performance metrics.
• Construct intuitive dashboards and reports to present evaluation results, facilitating straightforward comparisons that highlight both improvements and regressions of the ML components and the overall system.
• Develop and maintain continuous testing and monitoring systems to guarantee the integrity and resilience of our data and associated data pipelines.
• Develop data mining tools with applied ML techniques to support data discovery needs from Autonomy including Perception, Behavior, and Mapping
• Develop data annotation tools to support first-party and third-party labeling workforce to provide high fidelity perception, mapping, and driving trajectory labels
• Scale data annotation labels with applied State-of-the-art ML techniques

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Number of Employees: 501-1,000 employees